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FINAL PROJECT
MODULE : Quantitative Technique of Business (QTB)
Program: M.COM– A 1
Submitted By: 11321
Submitted To: Miss SAIRA MAJEED
Submitted On: 21.03.11
DEDICATION
ALL PRAISES FOR ALMIGHTY GOD ,THE CREATOR OF THE WORLDS AND THE HEAVENS.....I DEDICATE THIS FEEBLE WORK TO MY BELOVED PARENTS ,LIVING LEGENDS OF EXCELLENCE FOR MY LIVE WITHOUT THEIR KNOWLEDGE AND WISDOM AND GUIDANCE,I WOULD NOT HAVE ACHIEVED THE GOAL I HAVE STRIVED FOR….AND TO ALL THOSE WHO PRAY FOR ME…
Acknowledgement
Project in any field of study is the kind of achievement for which every student is looking for and thinking upon throughout his academic session that what it should be & how should it be completed. It is definitely a keen desire of every student to full fill his requirement. It needs through study untiring efforts, hard work with full devotion towards the cause and last but not the least proper guidance and corporation from seniors and instructors.
I extend my gratitude to “Miss Saira Majeed” whose guidance throughout the project and broadened vision by her ample experience and served as a lighthouse in this incredible venture for completion of the project.
CONTENTS
1- Introduction to employee turnover………………………………..032- Variables of Employee Turnover
And variables denoted by…………….………………………………………..04
3- Explanation of variables and theirrelationship with Employee Turnover………………………………05-07
4- Questionnaires…………………………………………………………………………………….08-125- Minitab analysis on individual basis…………..
………………………………………………………………………………………………13-546- Stat graphic Simple regression……………………………………………55-707- Stat graphic Multiple regression…………………………………….71-728- Model building………………………………………………………………………………………73-759- Comparison of collective and individual
variables on theoretical and model basis……………….76
____________
EMPLOYEE TURNOVER
Introduction:
Employee turnover is the number of permanent employees leaving the company within the reported period versus the number of actual active permanent employees on the last day of the previous reported period.
Definition:
“The ratio of the number of worker that had to be replaced in a given time period to the average number of workers.”
Explanation:
The number of leaves that are included in employee turnover only includes natural turnover (resignation, termination, retirement etc).
It does not reflect any redundancies. Planned redundancies are reported and explained separately if relevant for employee turnover.
___________________
LIST OF VARIABLES
1- Salary.2- Performance appraisals.3- Working environment.4- Employee motivation.5- Personal growth.6- Employee management.
7- Job Satisfaction.8- Promotional Opportunities.9- Matching jobs to people.10- Staff training and development.11- Team working.12- Incentives.
Variables used in software’s
1- Salary………………………………………………………………………………………… X1
2- Performance appraisals……………………………………………… X2
3- Working environment……………………………………………………… X3
4- Employee motivation……………………………………………………… X4
5- Job Satisfaction……………………………………………………………… X5
6- Promotional Opportunities……………………………………… X6
7- Matching jobs to people…………………………………………… X7
8- Staff training and development………………..…… X8
9- Team working………………………………………………..……….………. X9
10-Incentives……………………………………………..…………..…………… X10
_________________
EXPLANATION OF VARIABLES AND THEIR RELATIONSHIP WITH EMPLOYEE TURNOVER
1- Salary:Salary is remuneration or amount of money paid to workers or employees for their services and is measured on monthly basis not hourly as in wages.
Affect:
Less salary causes Employee Turnover.
2- Performance appraisals:Performance appraisal is sort of method by which the job performance is evaluated in tern of quality, quantity, cost and time through which employee’s success or failure is analyzed.
Affect:
Low performance appraisals cause Employee Turnover.
3- Working environment:A work environment can be identified as the place that one works. i.e. in an office building in cabin, at home at the kitchen table, from a car or truck, at a construction site. All are work environments.Affect:
Bad working environment causes Employee Turnover.
4- Employee motivation:Motivation refers to the initiation, direction, intensity and determination of human behavior.
Affect:
Lack of employee motivation causes Employee Turnover.
5- Personal growth:Employee’s responsibilities in the organization should help them achieve their personal goals. Organizations cannot keep aside the individual goals of employees and foster/promote organizations goals. Employees’ priority is to work for them and later on comes the organization. If they are not satisfied with their growth, they will not be able to contribute in organization’s growth.
Affect:
Lack of personal growth causes Employee Turnover.
6- Employee management:Employee Management means to provide guidance to employees in order to examine internal control and to avoid fraud.
Affect:
Poor employee management causes Employee Turnover.
7- Job Satisfaction:Job satisfaction describes how content an individual is with his or her job. According to my perspective happier people are more satisfied with their jobs.
Affect:
Less job satisfaction causes Employee Turnover.
8- Promotional Opportunities: Promotional opportunities mean encouragement of growth or progress. And due to effective and efficient work employees are given promotional opportunities.
Affect:
But Less Promotional opportunities cause Employee Turnover.
9- Matching jobs to people:Matching jobs to people needs proper management skills to organize their organization by putting right persons on right jobs e.g. division of managers according to their skills.
Affect:
Less matching jobs to people cause Employee Turnover.
10- Staff training and development:Staff training and development plays a vital role in introducing new concepts e.g. bringing an advance mode computer system in an organization or introducing new software’s requires proper training of staff.
Affect:
Less or not appropriate staff training and development cause Employee Turnover
11- Team working:Team working means managing people to see that they get the work done satisfactory. Remember, managers are not paid to have all the ideas that are necessary to keep their section working well, but they are paid to make sure that there are enough ideas to make things work and go on working.
Affect:
Less team working cause Employee Turnover
12- Incentives:An incentive can be in term of bonus or an additional payment to employees for high productivity. It is a sort of motivation.Affect:
But less incentives cause Employee Turnover.
_____________________
QUESTIONNAIRES
You are kindly requested to complete this questionnaire by encircling bullets so that we can get your perspective for our knowledge.
1- NAME _______________________
2- AGE
20 to 30. 30 to 40. 40 to 50. 50 to above.
3- Gender. Male. Female.
4- What categories best describes your job? Officer/Director/Manager/Supervisor. Group Leader. Customer Services. Sales Reps. Student. Other.
5- Education. Primary/Matriculation. Intermediate. Bachelors. Master/M Phil. Other.
6- Income Level. Rs 10000 to 20000. Rs 20000 to 30000. Rs 30000 to 40000. Rs 40000 to above. NIL.
7- Company benefit is a factor that plays a significant role in employee turnover. Agree. Strongly Agree. Neutral. Disagree. Strongly Disagree.
8- Salary is an important negotiator but by handling it wrong you can blow the Job offer or go to work at far less than you might have gotten? Agree. Strongly Agree. Neutral.
Disagree. Strongly Disagree.
9- Performance review is one of the factors that lowers the morale/confident or contributes to factors leading employee turnover? Agree. Strongly Agree. Neutral. Disagree. Strongly Disagree.
10- Do seniors encourage and allow working to the best of our abilities? Agree. Strongly Agree. Neutral. Disagree. Strongly Disagree.
11- Motivated employees always look for the better way to do job and are more quality oriented and productive/fruitful? Agree. Strongly Agree. Neutral. Disagree. Strongly Disagree.
12- Self-knowledge is one common goal that will help everyone achieve personal success YES. NO.
13- Is it possible for an employee to "fast track" or find short cut to achieve promotion unofficially? YES. NO.
14- Effective employee management and leadership allow you to capitalize on the strengths of other employees and their ability to contribute to the accomplishment of work goals.
Agree. Strongly Agree. Neutral. Disagree. Strongly Disagree.
15-
JOB CHARACTERISTICS
Impact
CRITICAL PSYCHOLOGICAL STATES
Skill Variety Task Identity & Task Significance
Experienced meaningfulness
Autonomy
Experienced
Responsibity for outcomes
& Feedback Knowledge of the actual results
20% to 40% 40% to 60% 60% to 80% 80% to above.
16- Many businesses find the over 60's age group hard to reach with traditional marketing and advertising, but Seniors Business Discount Card scheme makes it easy.
Agree. Strongly Agree. Neutral. Disagree. Strongly Disagree.
17- All positions and all employees are not equally key. Agree. Strongly Agree. Neutral. Disagree. Strongly Disagree.
18- The quality and variety of the employee training you provide is key for motivation. Agree. Strongly Agree. Neutral. Disagree. Strongly Disagree.
19- Teamwork involves working confidently within a group, contributing your own ideas effectively, taking a share of responsibility. Agree. Strongly Agree. Neutral. Disagree. Strongly Disagree.
20- People offering incentives are often unable to predict all of the ways that people will respond to them Agree. Strongly Agree. Neutral. Disagree. Strongly Disagree.
Thank you for giving your precious time.
___________________________
INDIVIDUAL BASIS DESCRIPTIVE ANALYSIS AND GRAPHS ON MINITAB
Y as Employee turnover and Salary as X1
Reporting Histogram of Y on X1
INTERPRETATION:
The histogram with curve of y and X1 shows one hump but humps are slightly clustered towards right and are negatively skewed.
Reporting Box plot of Y on X1
INTERPRETATION:
Box plot of Y is negatively skewed where as Box plot of X1 negatively skewed and the dot in box plot shows the extreme value. And is not fulfilling the properties of normal distribution.
Reporting Dotplot of Y on X1
INTERPRETATION:
The above Dot plot is of Y and X1 and in both plots bubbles are horizontally shown same like a straight line and have an exact or clear relationship.
Reporting Descriptive Statistics of Y on X1
INTERPRETATION:
The above descriptive statistics of Y shows that mean = 4.333 and median = 4.0000 which shows that there is a slight difference between mean and median due to which hump is slightly towards right.
INTERPRETATION:
The above descriptive statistics of X1 shows that mean = 3.333 and median = 3.0000 and have a slight difference of .333 between mean and median due to which hump is slightly towards right.
Y as Employee turnover and Performance appraisals as X2
Reporting Histogram of Y on X2
INTERPRETATION:
The histogram with curve of y and X2 shows one hump but hump of Y have a slight move towards right but X2 histogram shows the values are cluster towards right and is negatively skewed and is not fulfilling the properties of normal distribution.
Reporting Box plot of Y on X2
INTERPRETATION:
Box plot of Y is negatively skewed and is not fulfilling the properties of normal distribution where as Box plot of X2 shows different points horizontally located and just one value shows the trend of mean.
Reporting Dotplot of Y on X2
INTERPRETATION:
The above Dot plot is of Y and X2 and in both plots bubbles are horizontally shown same like a straight line and have an exact or clear relationship.
Reporting Descriptive Statistics of Y on X2
INTERPRETATION:
The above descriptive statistics of Y shows that mean = 4.333 and median = 4.0000 which shows that there is a slight difference between mean and median due to which hump is slightly towards right.
INTERPRETATION:
The above descriptive statistics of X2 shows that mean = 3.900 and median = 4.0000 and have a slight difference of .1 between mean and median due to which hump is slightly towards right.
Y as Employee turnover and Working environment as X3
Reporting Histogram of Y on X3
INTERPRETATION:
The histogram with curve of y and X3 shows one hump but humps are slightly clustered towards right and are negatively skewed.
Reporting Boxplot of Y on X3
INTERPRETATION:
Box plot of Y is negatively skewed where as Box plot of X3 is also negatively and is not fulfilling the properties of normal distribution means (means is not equal to median is not equal to mode.)
Reporting Dotplot of Y on X3
INTERPRETATION:
The above Dot plot is of Y and X3 and in both plots bubbles are horizontally shown same like a straight line and have an exact or clear relationship.
Reporting Descriptive Statistics of Y on X3
INTERPRETATION:
The above descriptive statistics of Y shows that mean = 4.333 and median = 4.0000 which shows that there is a slight difference between mean and median due to which hump is slightly towards right.
INTERPRETATION:
The above descriptive statistics of X3 shows that mean = 3.900 and median = 4.0000 and have a slight difference of .1 between mean and median due to which hump is slightly towards right.
Y as Employee turnover and Employee motivation as X4
Reporting Histogram of Y on X4
INTERPRETATION:
The histogram with curve of y and X4 shows one hump but humps are slightly clustered towards right and are negatively skewed.
Reporting Box plot of Y on X4
INTERPRETATION:
Box plot of Y and X4 are negatively skewed and is not fulfilling the properties of normal distribution means (means is not equal to median is not equal to mode.
Reporting Dotplot of Y on X4
INTERPRETATION:
The above Dot plot is of Y and X4 and in both plots bubbles are horizontally shown same like a straight line and have an exact or clear relationship.
Reporting Descriptive Statistics of Y on X4
INTERPRETATION:
The above descriptive statistics of Y shows that mean = 4.333 and median = 4.0000 which shows that there is a slight difference between mean and median due to which hump is slightly towards right.
INTERPRETATION:
The above descriptive statistics of X4 shows that mean = 4.26667 and median = 4.0000 and have a slight difference of .26667 between mean and median due to which hump is slightly towards right.
Y as Employee turnover and Job Satisfaction as X5
Reporting Histogram of Y on X5
INTERPRETATION:
The histogram with curve of y and X5 shows one hump but humps are slightly clustered towards right and are negatively skewed.
Reporting Boxplot of Y on X5
INTERPRETATION:
Box plot of Y are negatively skewed and is not fulfilling the properties of normal distribution means (means is not equal to median is not equal to mode). Whereas X5 is fulfilling the properties of normal distribution means (means is equal to median is equal to mode) and have exact are deterministic relationship.
Reporting Dotplot of Y on X5
INTERPRETATION:
The above Dot plot is of Y and X5 and in both plots bubbles are horizontally shown same like a straight line and have an exact or clear relationship.
Reporting Descriptive Statistics of Y on X5
INTERPRETATION:
The above descriptive statistics of Y shows that mean = 4.333 and median = 4.0000 which shows that there is a slight difference between mean and median due to which hump is slightly towards right.
INTERPRETATION:
The above descriptive statistics of X5 shows that mean = 2.53333 and median = 2.0000 and have a slight difference of .53333 between mean and median due to which hump is slightly towards right.
Y as Employee turnover and Promotional Opportunities as X6
Reporting Histogram of Y on X6
INTERPRETATION:
The histogram with curve of y shows one hump but X6 is approximately in middle there is just a point difference due to which mean is not equal to median is not equal to mode
Reporting Box plot of Y on X6
INTERPRETATION:
Box plot of Y are negatively skewed and is not fulfilling the properties of normal distribution means (means is not equal to median is not equal to mode). Whereas X6 have a point which is outlier and shows that mean is not equal to median is not equal to mode).
Reporting Dot plot of Y on X6
INTERPRETATION:
The above Dot plot is of Y and X6 and in both plots bubbles are horizontally shown same like a straight line and have an exact or clear relationship.
Reporting Descriptive Statistics of Y on X6
INTERPRETATION:
The above descriptive statistics of Y shows that mean = 4.333 and median = 4.0000 which shows that there is a slight difference between mean and median due to which hump is slightly towards right.
INTERPRETATION:
The above descriptive statistics of X6 shows that mean = 3.3000 and median = 3.0000 and have a slight difference of .3 between mean and median due to which hump is slightly towards right and is not fulfilling the condition of normal distribution.
Y as Employee turnover and matching jobs to people as X7
Reporting Histogram of Y on X7
INTERPRETATION:
The histogram with curve of y shows one hump but X7 is approximately in middle there is just a point difference due to which mean is not equal to median is not equal to mode.
Reporting Boxplot of Y on X7
INTERPRETATION:
Box plot of Y are negatively skewed. Whereas X7 is not fulfilling the condition of normal distribution and shows that mean is not equal to median is not equal to mode.
Reporting Dotplot of Y on X7
INTERPRETATION:
The above Dot plot is of Y and X7 and in both plots bubbles are horizontally shown same like a straight line and have an exact or clear relationship.
Reporting Descriptive Statistics of Y on X7
INTERPRETATION:
The above descriptive statistics of Y shows that mean = 4.333 and median = 4.0000 which shows that there is a slight difference between mean and median due to which hump is slightly towards right.
INTERPRETATION:
The above descriptive statistics of X7 shows that mean = 3.3667 and median = 3.5000 and have a slight difference between mean and median due to which hump is slightly towards right and is not fulfilling the condition of normal distribution.
Y as Employee turnover and Staff training and development as X8
Reporting Histogram of Y on X8
INTERPRETATION:
The histogram with curve of y shows one hump but X8 is approximately in middle there is just a point difference due to which mean is not equal to median is not equal to mode.
Reporting Boxplot of Y on X8
INTERPRETATION:
Box plot of Y and X8 are negatively skewed and are not fulfilling the condition of normal distribution and shows that mean is not equal to median is not equal to mode.
Reporting Dotplot of Y on X8
INTERPRETATION:
The above Dot plot is of Y and X8 and in both plots bubbles are horizontally shown same like a straight line and have an exact or clear relationship.
Reporting Descriptive Statistics of Y on X8
INTERPRETATION:
The above descriptive statistics of Y shows that mean = 4.333 and median = 4.0000 which shows that there is a slight difference between mean and median due to which hump is slightly towards right.
INTERPRETATION:
The above descriptive statistics of X8 shows that mean = 4.3667 and median = 4.0000 and have a slight difference between mean and median due to which hump is slightly towards right and is not fulfilling the condition of normal distribution.
Y as Employee turnover and Team working as X9
Reporting Histogram of Y on X9
INTERPRETATION:
The histogram with curve of y shows one hump but X9 is negatively skewed or upward bias means negative extreme values.
Reporting Boxplot of Y on X9
INTERPRETATION:
Box plot of Y are negatively skewed and is not fulfilling the properties of normal distribution means (means is not equal to median is not equal to mode). Whereas X9 have a point which is outlier and shows that mean is not equal to median is not equal to mode).
Reporting Dotplot of Y on X9
INTERPRETATION:
The above Dot plot is of Y and X9 and in both plots bubbles are horizontally shown same like a straight line and have an exact or clear relationship.
Reporting Descriptive Statistics of Y on X9
INTERPRETATION:
The above descriptive statistics of Y shows that mean = 4.333 and median = 4.0000 which shows that there is a slight difference between mean and median due to which hump is slightly towards right.
INTERPRETATION:
The above descriptive statistics of X9 shows that mean = 4.5000 and median = 5.0000 and have a difference between mean and median due to which hump is slightly towards right and is not fulfilling the condition of normal distribution.
Y as Employee turnover and Incentives as X10
Reporting Histogram of Y on X10
INTERPRETATION:
The histogram with curve of y shows one hump but X10 has a slight difference due to which it is not fulfilling the properties of normally distribution.
Reporting Boxplot of Y on X10
INTERPRETATION:
Box plot of Y are negatively skewed and is not fulfilling the properties of normal distribution means (means is not equal to median is not equal to mode). Whereas X10 is fulfilling the properties of normal distribution means (means is equal to median is equal to mode) and have exact are deterministic relationship.
Reporting Dotplot of Y on X10
INTERPRETATION:
The above Dot plot is of Y and X10 and in both plots bubbles are horizontally shown same like a straight line and have an exact or clear relationship.
Reporting Descriptive Statistics of Y on X10
INTERPRETATION:
The above descriptive statistics of Y shows that mean = 4.333 and median = 4.0000 which shows that there is a slight difference between mean and median due to which hump is slightly towards right
INTERPRETATION:
The above descriptive statistics of X10 shows that mean = 3.83333 and median = 4.0000 and have a slight difference between mean and median due to which hump is slightly towards right.
SIMPLE REGRESSION WITH GRAPHS AND PLOTS ON STAT GRAPHICS
Y as Employee turnover and Salary as X1
Regression Analysis - Linear model: Y = a + b*X
--------------------------------------------------------------------------
Dependent variable: Y
Independent variable: X1
--------------------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
--------------------------------------------------------------------------
Intercept 4.25 0.413716 10.2728 0.0000
Slope 0.025 0.119429 0.209329 0.8357
__________________________________________________________________________
Analysis of Variance
--------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio p-Value
--------------------------------------------------------------------------
Model 0.0166667 1 0.0166667 0.04 0.8357
Residual 10.65 28 0.380357
--------------------------------------------------------------------------
Total (Corr.) 10.6667 29
Correlation Coefficient = 0.0395285
R-squared = 0.15625 percent
Standard Error of Est. = 0.616731
INTERPRETATION
The equation of the fitted model is Y = 4.25 + 0.025* X1
Result shows that if X1 changes by one unit y will increase by 0.025 units
The R-Squared statistic indicates that the model as fitted explains
0.15625% of the variability in Y. The correlation coefficient equals
0.0395285, indicating a relatively weak relationship between the
variables. Whereas standard error is 0.616731
HISTOGRAM WITH POLYGON REPRESENTING Y ON X 1
INTERPRETATION:
The above histogram with polygon shows random relationship between dependent and independent variable and cannot figure out exact relationship due to ups and downs.
Y as Employee turnover and Performance appraisals as X2
Histogram for Y
Y
frequency
2.9 3.3 3.7 4.1 4.5 4.9 5.30
4
8
12
16
Regression Analysis - Linear model: Y = a + b*X
----------------------------------------------------------------
Dependent variable: Y
Independent variable: X2
----------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
----------------------------------------------------------------
Intercept 3.64611 0.500247 7.28862 0.0000
Slope 0.176211 0.125192 1.40753 0.1703
----------------------------------------------------------------
Analysis of Variance
----------------------------------------------------------------
Source Sum of Squares DF Mean Square F-Ratio P-Value
----------------------------------------------------------------
Model 0.704846 1 0.704846 1.98 0.1703
Residual 9.96182 28 0.355779
----------------------------------------------------------------
Total (Corr.) 10.6667 29
Correlation Coefficient = 0.257059
R-squared = 6.60793 percent
Standard Error of Est. = 0.596472
INTERPRETATION
The equation of the fitted model is Y = 3.64611 + 0.176211*X2
Result shows that if X2 changes by one unit y will increase by 0.176211 units.
The R-Squared statistic indicates that the model as fitted explains 6.60793% of the variability in Y. The correlation coefficient equals 0.257059, indicating a relatively weak relationship between the variables. Whereas standard error is 0.596472.
HISTOGRAM WITH POLYGON REPRESENTING Y ON X 2
INTERPRETATION:
The above histogram with polygon shows random relationship between dependent and independent variable and cannot figure out exact relationship due to ups and downs.
________________________________________________________________
Y as Employee turnover and Working environment as X3
Histogram for Y
Y
frequency
2.9 3.3 3.7 4.1 4.5 4.9 5.30
4
8
12
16
Regression Analysis - Linear model: Y = a + b*X
----------------------------------------------------------------
Dependent variable: Y
Independent variable: X3
----------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
----------------------------------------------------------------Intercept 3.65389 0.443921 8.23095 0.0000
Slope 0.174216 0.110407 1.57795 0.1258
--------------------------------------------------------------
Analysis of Variance
----------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
----------------------------------------------------------------
Model 0.87108 1 0.87108 2.49 0.1258
Residual 9.79559 28 0.349842
----------------------------------------------------------------
Total (Corr.) 10.6667 29
Correlation Coefficient = 0.285769
R-squared = 8.16638 percent
Standard Error of Est. = 0.591475
INTERPRETATION:
The equation of the fitted model is Y = 3.65389 + 0.174216*X3
Result shows that if X3 changes by one unit y will increase by 0.174216 units.
The R-Squared statistic indicates that the model as fitted explains8.16638% of the variability in Y. The correlation coefficient equals 0.285769, indicating a relatively weak relationship between the variables. Whereas standard error is 0.591475.
HISTOGRAM WITH POLYGON REPRESENTING Y ON X3
INTERPRETATION:
The above histogram with polygon shows random relationship between dependent and independent variable and cannot figure out exact relationship due to ups and downs.
Y as Employee turnover and Employee motivation as X4
Histogram for X3
X3
frequency
1.8 2.8 3.8 4.8 5.8 6.80
2
4
6
8
10
12
Regression Analysis - Linear model: Y = a + b*X
----------------------------------------------------------------
Dependent variable: Y
Independent variable: X4
----------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
----------------------------------------------------------------
Intercept 5.05042 0.656416 7.69394 0.0000
Slope -0.168067 0.15166 -1.10818 0.2772
-----------------------------------------------------------------
Analysis of Variance
----------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
----------------------------------------------------------------
Model 0.448179 1 0.448179 1.23 0.2772
Residual 10.2185 28 0.364946
----------------------------------------------------------------
Total (Corr.) 10.6667 29
Correlation Coefficient = -0.20498
R-squared = 4.20168 percent
Standard Error of Est. = 0.604108
INTERPRETATION:
The equation of the fitted model is Y = 5.05042 - 0.168067*X4 Result shows that if X4 changes by one unit y will increase by 0.168067 units. The R-Squared statistic indicates that the model as fitted explains 4.20168% of the variability in Y. The correlation coefficient equals -0.20498, indicating a relatively weak relationship between the variables. Whereas standard error is 0.604108.
HISTOGRAM WITH POLYGON REPRESENTING Y ON X 4
INTERPRETATION:
The above histogram with polygon shows random relationship between dependent and independent variable and cannot figure out exact relationship due to ups and downs.
Histogram for Y
Y
frequency
2.9 3.3 3.7 4.1 4.5 4.9 5.30
4
8
12
16
Y as Employee turnover and Job Satisfaction as X5
Regression Analysis - Linear model: Y = a + b*X
----------------------------------------------------------------
Dependent variable: Y
Independent variable: X5
----------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
----------------------------------------------------------------
Intercept 3.9863 0.365452 10.9079 0.0000
Slope 0.136986 0.137475 0.996448 0.3276
--------------------------------------------------------------------
Analysis of Variance
----------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
----------------------------------------------------------------
Model 0.365297 1 0.365297 0.99 0.3276
Residual 10.3014 28 0.367906
----------------------------------------------------------------
Total (Corr.) 10.6667 29
Correlation Coefficient = 0.185058
R-squared = 3.42466 percent
Standard Error of Est. = 0.606553
INTERPRETATION:
The equation of the fitted model is Y = 3.9863 + 0.136986*X5
Result shows that if X5 changes by one unit y will increase by 0.136986 units.
The R-Squared statistic indicates that the model as fitted explains 3.42466% of the variability in Y. The correlation coefficient equals 0.185058, indicating a relatively weak relationship between the variables. Whereas standard error is 0.606553.
HISTOGRAM WITH POLYGON REPRESENTING Y ON X 5
INTERPRETATION:
The above histogram with polygon shows random relationship between dependent and independent variable and cannot figure out exact relationship due to ups and downs.
Histogram for Y
Y
frequency
2.9 3.3 3.7 4.1 4.5 4.9 5.30
4
8
12
16
Y as Employee turnover and Promotional Opportunities as X6
Regression Analysis - Linear model: Y = a + b*X
----------------------------------------------------------------
Dependent variable: Y
Independent variable: X6
----------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
----------------------------------------------------------------
Intercept 3.63369 0.374559 9.70124 0.0000
Slope 0.212014 0.108885 1.94715 0.0616
----------------------------------------------------------------
Analysis of Variance
----------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
----------------------------------------------------------------
Model 1.27208 1 1.27208 3.79 0.0616
Residual 9.39458 28 0.335521
----------------------------------------------------------------
Total (Corr.) 10.6667 29
Correlation Coefficient = 0.345337
R-squared = 11.9258 percent
Standard Error of Est. = 0.579242
INTERPRETATION:
The equation of the fitted model is Y = 3.63369 + 0.212014*X6
Result shows that if X6 changes by one unit y will increase by 0.212014 units.
The R-Squared statistic indicates that the model as fitted explains 11.9258% of the variability in Y. The correlation coefficient equals 0.345337, indicating a relatively weak. Whereas standard error is 0.579242
HISTOGRAM WITH POLYGON REPRESENTING Y ON X 6
INTERPRETATION:
The above histogram with polygon shows random relationship between dependent and independent variable and cannot figure out exact relationship due to ups and downs.
Histogram for Y
Y
frequency
2.9 3.3 3.7 4.1 4.5 4.9 5.30
4
8
12
16
Y as Employee turnover and Matching jobs to people as X7
Regression Analysis - Linear model: Y = a + b*X
----------------------------------------------------------------
Dependent variable: Y
Independent variable: X7
----------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
----------------------------------------------------------------
Intercept 4.14158 0.341507 12.1274 0.0000
Slope 0.0569569 0.0958291 0.594359 0.5570
----------------------------------------------------------------
Analysis of Variance
----------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
----------------------------------------------------------------
Model 0.132899 1 0.132899 0.35 0.5570
Residual 10.5338 28 0.376206
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Total (Corr.) 10.6667 29
Correlation Coefficient = 0.111621
R-squared = 1.24593 percent
Standard Error of Est. = 0.613356
INTERPRETATION:
The equation of the fitted model is Y = 4.14158 + 0.0569569*X7
Result shows that if X7 changes by one unit y will increase by 0.0569569 units.
The R-Squared statistic indicates that the model as fitted explains 1.24593% of the variability in Y. The correlation coefficient equals 0.111621, indicating a relatively weak relationship between the variables. Whereas standard error is 0.613356
HISTOGRAM WITH POLYGON REPRESENTING Y ON X 7
INTERPRETATION:
The above histogram with polygon shows random relationship between dependent and independent variable and cannot figure out exact relationship due to ups and downs.
Histogram for Y
Y
frequency
2.9 3.3 3.7 4.1 4.5 4.9 5.30
4
8
12
16
Y as Employee turnover and Staff training and development as X8
Regression Analysis - Linear model: Y = a + b*X
----------------------------------------------------------------
Dependent variable: Y
Independent variable: X8
----------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
----------------------------------------------------------------
Intercept 4.22108 0.756596 5.57904 0.0000
Slope 0.0257069 0.171335 0.150039 0.8818
----------------------------------------------------------------
Analysis of Variance
----------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
----------------------------------------------------------------
Model 0.00856898 1 0.00856898 0.02 0.8818
Residual 10.6581 28 0.380646
----------------------------------------------------------------
Total (Corr.) 10.6667 29
Correlation Coefficient = 0.0283433
R-squared = 0.0803342 percent
Standard Error of Est. = 0.616965
INTERPRETATION:
The equation of the fitted model is Y = 4.22108 + 0.0257069*X8
Result shows that if X8 changes by one unit y will increase by 0.0257069 units.
The R-Squared statistic indicates that the model as fitted explains 0.0803342% of the variability in Y. The correlation coefficient equals 0.0283433, indicating a relatively weak relationship between the variables. Whereas standard error is 0.616965.
HISTOGRAM WITH POLYGON REPRESENTING Y ON X 8
INTERPRETATION:
The above histogram with polygon shows random relationship between dependent and independent variable and cannot figure out exact relationship due to ups and downs.
Histogram for Y
Y
frequency
2.9 3.3 3.7 4.1 4.5 4.9 5.30
4
8
12
16
Y as Employee turnover and Team working as X9
Regression Analysis - Linear model: Y = a + b*X
----------------------------------------------------------------
Dependent variable: Y
Independent variable: X9
----------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
----------------------------------------------------------------
Intercept 4.71631 0.579245 8.14217 0.0000
Slope -0.0851064 0.126301 -0.673835 0.5059
----------------------------------------------------------------
Analysis of Variance
----------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
----------------------------------------------------------------
Model 0.170213 1 0.170213 0.45 0.5059
Residual 10.4965 28 0.374873
----------------------------------------------------------------
Total (Corr.) 10.6667 29
Correlation Coefficient = -0.126323
R-squared = 1.59574 percent
Standard Error of Est. = 0.612269
INTERPRETATION:
The equation of the fitted model is Y = 4.71631 - 0.0851064*X9
Result shows that if X9 changes by one unit y will increase by 0.168067 units The R-Squared statistic indicates that the model as fitted explains 1.59574% of the variability in Y. The correlation coefficient equals -0.126323, indicating a relatively weak relationship between the variables. Whereas standard error is 0.612269.
HISTOGRAM WITH POLYGON REPRESENTING Y ON X 9
INTERPRETATION:
The above histogram with polygon shows random relationship between dependent and independent variable and cannot figure out exact relationship due to ups and downs.
Histogram for Y
Y
frequency
2.9 3.3 3.7 4.1 4.5 4.9 5.30
4
8
12
16
Y as Employee turnover and Incentives as X10
Regression Analysis - Linear model: Y = a + b*X
----------------------------------------------------------------
Dependent variable: Y
Independent variable: X10
----------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
----------------------------------------------------------------
Intercept 3.98165 0.562352 7.08036 0.0000
Slope 0.0917431 0.143768 0.638133 0.5286
----------------------------------------------------------------
Analysis of Variance
----------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
----------------------------------------------------------------
Model 0.152905 1 0.152905 0.41 0.5286
Residual 10.5138 28 0.375491
----------------------------------------------------------------
Total (Corr.) 10.6667 29
Correlation Coefficient = 0.119728
R-squared = 1.43349 percent
Standard Error of Est. = 0.612774
INTERPRETATION:
The equation of the fitted model is Y = 3.98165 + 0.0917431*X10
Result shows that if X10 changes by one unit y will increase by 0.0917431 units.
The R-Squared statistic indicates that the model as fitted explains 1.43349% of the variability in Y. The correlation coefficient equals 0.119728, indicating a relatively weak relationship between the variables. Whereas standard error is 0.612774.
HISTOGRAM WITH POLYGON REPRESENTING Y ON X 10
INTERPRETATION:
The above histogram with polygon shows random relationship between dependent and independent variable and cannot figure out exact relationship due to ups and downs.
Histogram for Y
Y
frequency
2.9 3.3 3.7 4.1 4.5 4.9 5.30
4
8
12
16
Multiple Regression Analysis on Stat Graphics
--------------------------------------------------------------------------
Dependent variable: Y
----------------------------------------------------------------
Standard T
Parameter Estimate Error Statistic P-Value
--------------------------------------------------------------------------
CONSTANT 2.06706 1.63796 1.26198 0.2222
X1 0.0546007 0.148508 0.36766 0.717
X2 0.250623 0.16329 1.53483 0.1413
X3 0.261568 0.154798 1.68974 0.1074
X4 -0.19548 0.201666 -0.969322 0.3446
X5 0.0185844 0.168276 0.11044 0.9132
X6 0.104358 0.147112 0.709381 0.4867
X7 0.020056 0.120711 0.166148 0.8698
X8 0.0151141 0.231948 0.0651619 0.9487
X9 0.0441014 0.18303 0.240951 0.8122
X10 0.0514776 0.162246 0.317282 0.7545
--------------------------------------------------------------------------
Analysis of Variance
--------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
--------------------------------------------------------------------------
Model 3.59315 10 0.359315 0.97 0.5021
Residual 7.07352 19 0.372291
-------------------------------------------------------------------------
Total (Corr.) 10.6667 29
R-squared = 33.6858 percent
R-squared (adjusted for d.f.) = 0.0 percent
Standard Error of Est. = 0.610156
Mean absolute error = 0.432037
Durbin-Watson statistic = 2.07889
INTERPRETATION:
The equation of the fitted model is
Y = 2.06706 + 0.0546007*X1 + 0.250623*X2 + 0.261568*X3 - 0.19548*X4 +
0.0185844*X5 + 0.104358*X6 + 0.020056*X7 + 0.0151141*X8 + 0.0441014*X9
+ 0.0514776*X10
The R-Squared statistic indicates that the model as fitted
explains 33.6858% of the variability in Y. The standard error of the estimate shows the standard deviation of the residuals to be 0.610156. Since the P-value in the ANOVA table is greater or equal to 0.10, there is not a statistically significant relationship between the variables at the 90% or higher confidence level.
Model building
X2( Performance appraisals ) included in analysis by making
comparison on multiple regression
X2
Analysis of Variance
-------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
--------------------------------------------------------------------------
Model 0.704846 1 0.704846 1.98 0.1703
Residual 9.96182 28 0.355779
--------------------------------------------------------------------------
INTERPRETATION:
In determining whether the model can be simplified, notice that the P-value on the independent variables is 0.1703, belonging to X2 and better than other variable.
X3
Analysis of Variance
--------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
--------------------------------------------------------------------------
Model 0.87108 1 0.87108 2.49 0.1258
Residual 9.79559 28 0.349842
INTERPRETATION:
In determining whether the model can be simplified, notice that the P-value on the independent variables is 0.1258, belonging to X2 and better than other variables.
X4
Analysis of Variance
--------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
--------------------------------------------------------------------------
Model 0.448179 1 0.448179 1.23 0.2772
Residual 10.2185 28 0.364946
INTERPRETATION:
In determining whether the model can be simplified, notice that the P-value on the independent variables is 0.2772, belonging to X2 and better than other variables
X5
Analysis of Variance
-----------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
-----------------------------------------------------------------------------
Model 0.365297 1 0.365297 0.99 0.3276
Residual 10.3014 28 0.367906
INTERPRETATION:
In determining whether the model can be simplified, notice that the P-value on the independent variables is 0.3276, belonging to X2 and better than other variables
X6
Analysis of Variance
--------------------------------------------------------------------------
Source Sum of Squares Df Mean Square F-Ratio P-Value
--------------------------------------------------------------------------
Model 1.27208 1 1.27208 3.79 0.0616
Residual 9.39458 28 0.335521
--------------------------------------------------------------------------
INTERPRETATION:
In determining whether the model can be simplified, notice that the P-value on the independent variables is 0.0616, belonging to X2 and better than other variables
Comparison of multiple and individual variables analysis on the basis of model and theoretical significance.
Y = a + bx2 + cx3 + dx4 + ex5 + fx6
Whereas y is dependent variable (Employee turnover) and independent variables X2 (Performance appraisal), X3 (Working environment), X4 (Employee motivation), X5 (Job satisfaction), X6 (Promotional opportunities).
The above equation is being generated by making brief analysis of 10 variables and the above 5 variables are selected as best among 10 just because of their p-value (The probability of accepting null hypothesis). Which are found less than other variables.
Overall analysis shows that performance appraisal, working environment, employee motivation, job satisfaction, and promotional opportunities affect employee turnover.
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