Presentation on Statistical

Analysis of Manufacturing and Processing Company

By Group :- B Date :- 15th July 2013

INTRODUCTION• Introduction to manufacturing company• Objectives of the study• Variables under study

Net worth per shareNet profitPaid up capital

• HypothesisNull hypothesis: There is no significant impact of Net

Profit and Paid up capital on Net worth per Share.Alternative hypothesis: There is significant impact of

Net profit and Paid up capital on Net worth per Share.Level of significance: 5%

• Methodologysecondary information and data

DESCRIPTIVE ANALYSIS• Descriptive statistics is the discipline of quantitatively

describing the main features of a collection of data or the quantitative description itself.

• Some measures that are commonly used to describe a data set are measures of central tendency and measures of variability or dispersion. Mean Median Mode Standard deviation

Box-plot summary• A box plot provide a graphical representation of the data

based on five number summary. Box-PlotMIN=-50.42MAX=444.04     Q1= -9.145 Q2= -0.62 Q3=19.0825   It indicates that it is right skewed. It is because the distance between

the median and the highest value is greater than distance between the lowest value and the median value. Right tail is longer than the left tail.

• Coefficient of variation (C.V)The coefficient of variation measures the scatter in the data relative to the mean. It is the measure of consistency of the data. The coefficient of variation denotes the variation or riskiness.

• SkewnessSkewness is the measure of asymmetry of the probability distribution of a real-valued random variable. It can be positive or negative, or even undefined. Skewness is an important consideration when examining investment returns

• KurtosisKurtosis measures whether the data is sharp or flat relative to a normal distribution. It focuses on how returns are ranged around the mean.

Descriptive statistics  Net worth per share Net profit Paid up capital

Mean -24.72 39.53 148.08

Standard Error 145.43 37.80 42.53

Median 83.10 -0.62 106.54

Mode N/A N/A N/A

Standard Deviation 503.79 130.95 147.34

Sample Variance 253800.19 17147.55 21710.41

Kurtosis 4.91 10.37 -0.43

Skewness -1.66 3.15 0.89

Range 2117.39 494.46 421.62

Minimum -1370.27 -50.42 12.93

Maximum 747.12 444.04 434.55

Sum -296.69 474.37 1777.01

Count 12.00 12.00 12.00

Interpretation

• Net worth per share The mean is -24.72 The median is 83.90 The standard deviation is 503.79, The skewness is -1.66, which shows that the data is left skewed. The minimum is worth per share is -1370.27 The maximum worth per share is 747.12. Since frequency is not available, mode cannot be calculated. The kurtosis is 4.91, which shows leptokurtic distribution.

• Net profitThe mean is 39.53 The median is 0.62The standard deviation is 130.95Since frequency is not available, mode cannot be

calculated. the minimum profit is -50.42 and maximum profit is

444.04 The skewness is 3.15, which shows that the data is right

skewed. The kurtosis is 10.37, which shows leptokurtic distribution.

• Paid up capital The mean is 148.08 The median is 106.54 The mode cannot be calculated here because of

unavailability of frequency. The standard deviation is 147.34 The skewness is 0.89 which shows that the data is right

skewed.The kurtosis is -0.43, which shows plautikurtic distributionThe minimum value is 12.93 and the maximum value is

434.55

CORRELATION AND REGRESSION ANALYSIS

• Correlation

correlation matrix Net worth per share Net profit Paid up capital

Net worth per share 1    

Net Profit 0.54 1  

Paid up capital 0.04 -0.21 1

Calculation of Variance Inflation Factor (VIF):  

Between paid up capital and net profitVIF = 1/ 1-r 2

= 1/ (1- (-0.21)2) = 1.05Since VIF between net profit and paid up capital is less than 10 the multi-co-linearity does not exist. Therefore we now compute the regression equation.

 

Regression• Regression is a way of describing how one variable, the outcome, is

numerically related to predictor variables.

Y = α+ β1x1+ β2x2+...+ βnxn

Regression table Coefficients Standard Error t Stat P-value

Net worth per share -192.20 205.90 -0.93 0.37

Net profit 2.21 1.08 2.04 0.07

Paid up capital 0.54 0.96 0.56 0.59

The estimated regression equation :Y= α+ β1 X1+β2 X2

Y= -192.20 + (2.21*X1) + (0.54*X2)

(-0.93) (2.04)* (0.56)Note: * signify the significance level at 1%.

• α = -192.20. It indicates that when net profit and paid up capital are zero, the net worth per share is -192.20 which indicates there is negative net worth per share or decreasing net worth per share.

• β1=2.21 indicates that if net profit is increased by 1 more unit then the net worth per share increases by 2.21 unit keeping paid up capital at its constant level.

• β2=0.54 indicates that if paid up capital is increased by 1 more unit then the net worth per share increases by 0.54 unit keeping net profit constant at its same level.

Regression Statistics

Multiple R 0.56

R Square 0.32

Adjusted R Square 0.17

Standard Error 460.32

Observations 12

ANOVA

Df SS MS F Significance F

Regression 2 884743.40 442371.70 2.09 0.18

Residual 9 1907058.67 211895.41    

Total 11 2791802.08      

Interpretation• R= 0.56 means the multiple correlation between the net worth

per share and net profit and paid up capital is 56%. • R2= 0.32 means 32% of variation in net worth per share is

explained by linear relationship of net profit and paid up capital, while 68% of variation remains unexplained.

• F= 2.09 using the 0.05 level of significance from the table the critical value of F distribution is more than the F statistical value, we accept the null hypothesis and conclude that the net worth per share is significantly related to the net profit and paid up capital.

CONCLUSION• P value of x variable 2 i.e.: Paid up capital is greater than the significance level so

there is no significant relation between Paid up capital and Net worth per share. • P value of x variable 1 i.e.: Net Profit is greater than the level of significance so

there is no significant relation between Net Profit and Net worth per share. • Since R2=32% these two factors are responsible to describe 32% of change in

return other remaining (68%) remains unexplained. • Now from the ANOVA table, we have F=2.09 which is smaller than the

F(table)=4.26 hence Null hypothesis is accepted. • Since there is no significant linear relationship between dependent variable

(Return) and independent variables (Net Profit and Paid Up Capital) Null hypothesis is accepted.

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