Report Draft (4)

7/29/2019 Report Draft (4)

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Table of Contents

Group members and list of work ............................................................................... 2

Introduction ................................................................................................................ 3

Collecting data ........................................................................................................... 4

Presenting and Summarizing data .............................................................................. 6

1. Subject................................................................................................................. 6

2. Number of absent classes per month .................................................................. 7

3. Average number of hours spent for self-study .................................................10

4. GPA ...................................................................................................................14

Regression model .....................................................................................................18

1. Descriptive statistics .........................................................................................18

2. Regression model ..............................................................................................18

Conclusion ...............................................................................................................22

Appendix ..................................................................................................................23


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Group members and list of workName Student ID Tasks % equivalent

Pham Ngoc Anh Collecting data

Preparing slides

13

Dang Thi Hien Writing "Introduction"

Designing survey

14

Hoang Thanh Ha Collecting data

Presenting

13

Phan Duy Hung 1001030153 Processing and Analyzing data

Writing "Regression model"

and "Average number of hours

spent for self - study"

25

Bui Kieu Dieu

Linh

1001010500 Processing and Analyzing data

Writing "Presenting and

Summarizing data"

25

Kim Le Ha Thanh Designing survey

Writing "Conclusion"

10

It should be note that all members of the group are serious, enthusiastic and hard -

working. They all did the tasks given well and before deadline. In fact, each

member could do equal y (which means sharing the same task for all 6 people), but

for the sake of the report's quality as well as time saving, we delegate the tasks

based on our strengths and weaknesses. Therefore, the percentage here is just arelative measure, and in terms of working attitude and efficiency, all members

could be regard as equivalent.


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Introduction

Education is one of the most fundamental aspects for individuals success in life. It

is also the best investment for people because well educated people would have

more opportunities to get promising jobs in the future. However, not many people

realize that importance and are wasting their time on other nonsensical reasons. To

be more specific, there are quite a variety of dangers which seduce students such as

video games, internet social programs, etc,.. But in this scope of our assignment,

we just focus on some main factors such as: being absent from the class due to the

weather, registering lots of lessons then quit from class several times, spending

least time on studying,...which affect directly to students of Foreign Trade

University (FTU), especially members of High Quality Classes of Finance and

Banking. From this view, the data would be closer and more accurate to our

findings.

This topic may be popular for researching at FTU, on the other hand, there has not

been a research for students of High Quality Programs in Finance and Banking

Faculty before. So that we decide to focus on this number of people and choose the

topic : Investigation of absent time of students and their average total marks

so as to figure out how important of studying hard, trying their best to get a good

result, giving optimistic attitude of learning,... After seeing the final output, it may

help a student look back his studying history and change the habits to be better at

university. Our purpose of doing this assignment is illustrating the important of

education, particularly the time at university for learners.

In our research, we use five methods of business statistics including collecting

data, presenting, summarizing, analyzing and forecasting in order to make our

studying as effective and informative as possible.


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Collecting data

In order to study the diligence of Foreign Trade University students of HighQuality Class, Faculty of Finance and Banking (a.k.a CLCTCNH), we collected

data in both direct and indirect way.

By the first method, our group including 6 people randomly chose some classes

and spontaneously asked several people to fill in the survey for us. In addition, we

created a online version then spread it through email and social network like

Facebook.

The overall students of CLCTCNH are about 600 students, and we tried to get at

least 10% of these to serve for our study.

And here is our survey we used to collect data

Investigation on students' studying habit

1. According to credit scale, how many subjects are you studying?* < 5 6 -8 >82. How many classes per week do you have? * 3. How much time do you spend on self-studying at home? *

4. How many classes per month are you absent from? * 5. Are you interested in studying in the class? * Yes No Only in some certain subjects


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6. Which thing(s) most make you want to skip a class? * Bad weather Classes without checking attendance Studying without understanding the lesson Busy with other activities Getting up late Other:7. Are you happy with your studying now? * No Yes Some subjects only8. Your average GPA (for the scale of 4) at the moment * 9. Which year are you in? K47 K48 K49 K50

The complete filled surveys will be showed latter in the appendix.


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Presenting and Summarizing data

1. SubjectAfter one week collecting data, we got 75 surveys filled, more than what we

expected. A quick glance at the pie chart below shows that of 4 kinds, 2nd year

students and 3rd year students were willing to answer the survey's question much

more than 1st year and 4th year students. This may be explained by the fact that

last year students are too busy with their work and graduation essay that they didn't

have time to answer these. For the 1st year students, we guess that since they

haven't learned courses as Economics or Business Statistic yet, so they didn't have

the motive to answer these.

11%

38%47%

4%

K47 K48 K49 K50


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2. Number of absent classes per month

Table of distribution

xi fi cumulative frequency relative frequency (%)

0 14 14 18.7%

1 12 26 16.0%

2 15 41 20.0%

3 4 45 5.3%

4 11 56 14.7%

5 9 65 12.0%

6 3 68 4.0%8 2 70 2.7%

10 2 72 2.7%

12 1 73 1.3%

16 1 74 1.3%

25 1 75 1.3%

From the above data, we calculated:

The range: R = largest valuesmallest value = 25 - 0 = 25This range tells us the difference between the largest and the smallest value

of the distribution is 25.

Although the absent classes per month of each students range from 0 to 25,

there are only 12 values, with the number of absent classes are mainly less

than 10 (which are account for 70% overall)

The arithmetic mean:

Mean = 253/75 = 3.37


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This number tells us the monthly average absent classes are 3.37, or in a

more sensible understanding, averagely, a CLCTCNH student takes 3 to 4

classes off per month.

The mean deviation

Mean deviation = 2.568

The average difference between the number of absent classes and the meanis 2.568

ModeThe mode of the data set is the value which has the largest frequency. From

the above table, we can see the rate which appears the most is 2, which has

the frequency of 15 times. The below graph also illustrates this fact

0

2

4

6

8

10

12

14

16

0 1 2 3 4 5 6 8 10 12 16 25

fi

1

n

i

i

x x

dn


9/23

This data can be understood as of the studied students, most of them choose

to be off 2 classes per month.

However, we should also note an interesting number that there are 18.7%

students never or hardly absent from any classes, which is only 1.3% less

than the mode of 2. Therefore, we have evidence to say that Finance and

Banking students are quite hard-working.

MedianBased on the table of distribution in which total frequency is 75, we can find

the middle item is the 38th

item, corresponding to the value of 2.

Median = 2 The variance

Variance = 63.403136

The average of squared discrepancies between each number of monthly

absent classes and the mean is 63.40

The standard deviation

Standard deviation = 2.821890458


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The coefficient of variation

Coefficient of variation = 83.65 %

3. Average number of hours spent for self-study


xi fiCumulative

frequency

Relative frequency

(%)

0 6 6 8 %

0.25 1 7 1.3 %

0.5 11 18 14.7 %

1 15 33 20 %

1.5 1 34 1.3 %

2 24 58 32 %

3 6 64 8 %

4 6 70 8 %

5 4 74 5.3 %

10 1 75 1.3 %

The following dot plot shows the frequency of values of time students spending on

self - studying


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From the above data, we calculated:

The range:R = largest valuesmallest value = 10- 0 = 10

This range tells us the difference between the largest and the smallest value

of the distribution is 10.

Although the number of hours spent on self-studying of each students range

from 0 to 10, there are only 10 values, with the number of hours are mainly

less than 10 (which are account for 70% overall)

The arithmetic mean:

Mean = 142.25/75=1.897

This number tells us the daily average hours spent on self-studying are

1.897, or in a more sensible understanding, averagely, a CLCTCNH student

spends about 2 hours a day on revising their home assignment.

0 2 4 6 8 10

Dotplot of hours spent on self-

studying


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The mean deviation

Mean deviation = 1.126

The average difference between the number of hours spent on self-studying

and the mean is 1.126

MedianThe median of the data set is the value of the item in the middle when the

data items are arranged in ascending order.Based on the table of distribution in which total frequency is 75, we can find

the middle item is the 38th

item, corresponding to the value of 2.

Median = 2

ModeThe mode of the data set is the value which has the largest frequency. From

the above table, we can see the rate which appears the most is 2, which has

the frequency of 24 times. The below graph also illustrates this fact

1

n

i

i

x x

d

n


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This data can be understood as of the studied students, most of them spend 2

hours per day on studying.

Mode = 2

As we can see from the graph and the table of frequency distribution, only

8% of students never spend their time at home on studying, which indicates

that there are still a large number of CLCTCNH students being aware oftheir task.

The variance

Variance = 2.617

The average of squared discrepancies between each number of monthly

absent classes and the mean is 2.617


0

5

10

15

20

25

30

0 0.25 0.5 1 1.5 2 3 4 5 10

fi


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Standard deviation = 1.618

The coefficient of variation

Coefficient of variation = 85.293 %

4. GPA


xi fi xi fi xi fi

2.67 1 3.19 1 3.42 2

2.8 2 3.2 10 3.47 1

2.83 1 3.22 3 3.48 1

2.88 1 3.23 2 3.49 1

2.9 2 3.24 1 3.5 1

2.91 1 3.25 1 3.54 2

2.93 1 3.27 1 3.62 1

2.97 1 3.28 1 3.64 1

3 3 3.3 4 3.65 1

3.03 1 3.31 2 3.67 2

3.04 2 3.34 1 3.76 1

3.1 2 3.35 2 3.79 1

3.13 1 3.38 2 3.8 1

3.15 1 3.4 3 3.9 2

3.17 1 3.41 1 4 1


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There are 45 values in this data set, so we create a table of grouped frequency

distribution in order to simplify it, which help readers easier to follow

GPA f

cummulative

frequency (%)

class mid

point (x)

2.67 up to 2.75 1 1.33% 2.71

2.76 up to 3.00 12 16.00% 2.88

3.01 up to 3.25 26 34.67% 3.13

3.26 up to 3.50 23 30.67% 3.38

3.51 up to 3.75 7 9.33% 3.63

3.76 up to 4.00 6 8.00% 3.88

Total 75 100.00%

Those can be illustrated by the following ogive:

1.33%

17.33%

52.00%

82.67%

92.00%100.00%

0.00%

20.00%

40.00%

60.00%

80.00%

100.00%

120.00%

2.67 up to

2.75

2.76 up to

3.00

3.01 up to

3.25

3.26 up to

3.50

3.51 up to

3.75

3.76 up to

4.00

Ogive of GPA


16/23

From the above statistic, we can calculate

The range : R = largest valuesmallest value = 4 - 2.67 = 1.33Class width: C= lower limit of class N+1 - lower limit class N = 3.01 - 2.76 =

0.25

With the available data, we grouped them into 6 classes, with the class range

of 0.25 and total range is 1.33. It should be noted that the GPA here is

calculated on the scale of 4, not 10 as usual. Therefore, 4 is the highest mark.

The arithmetic mean

Mean = 245.08/75 = 3.27

From the value calculated, we can generally understood as the standard

average GPA of a CLCTCNH student is 3.27

The mean deviation

md = 0.24So the average distance between the avarage GPA and GPA is 0.24

The mode ( )

Mode = 3.22

So the GPA that occurs most often of CLCTCNH student is 3.22


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The median

[ ] Median = 3.16

This number tells us the middle value of GPA in size order is 3.16

The variance

Variance = 0.082


Standard deviation= 0.287

The coefficient of the variance

Coefficient of variance = 8.77%

0

5

10

15

20

25

30

2.67 up to

2.75

2.76 up to

3.00

3.01 up to

3.25

3.26 up to

3.50

3.51 up to

3.75

3.76 up to

4.00

Histogram of GPA


18/23

Regression model

Analyzing the relationship between

GPA, number of absent classes and number of self - studying hours

1. Descriptive statisticsThe dependent variable we use in this model is GPA and the independent variable

is the number of classes students are absent from and the number of hours spent for

self-study.

To specify,

y : GPA

x1 : The number of classes students are absent from

x2 : The number of hours spent for self-study

2. Regression model

We can easily calculate ^0 and

^1 (or b0 and b1) of the regression function by

using the calculation of Excel and testing the result with Gretl software.

Step 1: Calculating by Excel

We have:

The population model:y = 0 + 1x1+ 2x2 +


19/23

Where, 0 : intercept of y

1x1 + 2x2 : population slope

: random error

The estimated multiple regression model isy

^= b0 + b1x1 + b2x2

Where, y^: estimated (predicted) value of y

b0 : estimated intercept

b1x1 + b2x2 : estimated slope coefficients

The formula of b0, b1 and b2 as following:

y = nb0 + b1x 1 + b2x 2

and x 1y = b0x 1 + b1x12

+ b2x 1x2

and x 2y = b0x 2 + b1x 1x2 + b2x 22

We have:

{ b0 = 3.31947

b1 = -0.0323693

b2 = 0.0739471

The estimated model is y^ = 3.31947 - 0.0323693x1 + 0.0739471 x2


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Step 2: Testing the calculation by Gretl:

Model 1: OLS, using observations 1-75

Dependent variable: GPA_Y

Coefficient Std. Error t-ratio p-value

const 3.31947 0.133021 24.9546


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R2= 0.072181 means that the variation in the independent variables is able to

explain 7.2181% of the total variation in the dependent variable.

According to the final result we can jump to conclusion as following :

- As we can see, b0 = 3.31947 reflects that the GPA is not affected by not only the

number of classes students are absent from and the number of hours spent for self-

study but also other factors.

- Equation (*) illustrates the fact that the number of hours that student skipped

classes has a negative effect on their GPA. One hour of being absent from classes

makes GPA decrease 0.0323693 if other factors remain unchanged.

- According to equation (*), we can see the obviously positive relationship between

the hours that student spent on self- studying and their GPA. A coefficient of

0.0739471 means that when the time for self studying increases one more hour, the

students GPA will also increase 0.0739471.


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Conclusion

Due to limited time and resource, our group chose to investigate only in small area

High quality class, Faculty of Finance and Banking instead of the whole

university or even in other universities. If having any more time for us, our group

believes that we will be able collect more information, more data as a result, more

accurate results for this survey.

In addition, the hours students spent on self-studying and the number of classes

students are absent from have a positive relationship with their GPA. With the

result of this survey and the data collected, there are convincing evident that ifstudents want to improve their GPA, they should be more diligent. In specific, we

students need to spend much time to improve knowledge by studying hard at

school, listening carefully to the teachers lecture, doing homework regularly and

moreover, the number of hours spending on self-studying are very extremely

important for each students.

Finally, through this investigation, we not only believe to bring application tostudents and teacher but also gained ourselves helpful and practical knowledge,

which can be used many times afterward.


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Appendix

GPA AbsentSelf-

studyGPA Absent

Self-

studyGPA Absent

Self-

study

2.88 10 0 3.2 2 1 3.27 5 4

3.2 2 2 2.67 4 0.5 3.2 5 0.5

3.54 4 3 2.93 2 2 3.76 3 10

2.91 5 2 8.5 0 3 3.04 25 3

3.22 2 5 3.22 0 1 3.8 1 0.5

3.13 12 0 3.48 1 1 3.3 2 2

3.03 5 0 3.4 5 1 3.42 2 0.5

3.2 10 0 2.9 7 2 3.2 4 2

3.34 4 1 3.28 7 2 3.79 0 4

3.1 2 0.5 3.22 4 0.5 3.23 0 0.25

3.47 4 1.00 3.38 1 0.5 3.17 4 2

3.24 0 1 3.9 1 2 3 2 2

2.8 2 1 3.19 5 1.5 3.65 1 3

2.97 3 1 3.31 7 5 3.3 8 23.49 2 1 3.54 8 5 3.31 4 2

3.2 1 4 2.9 5 2 3.42 0 2

3.3 2 0 3.62 0 3 2.8 5 4

3.1 3 0.5 3.5 1 0.5 3.2 2 1

3.23 0 2 3.67 2 2 3.25 4 2

3 5 2 3.38 1 1 4 0 3

3.41 3 2 3.2 4 2 3.35 2 2

3.04 1 2 3.67 0 1 3.35 16 0

2.83 1 2 3.2 1 1 3.3 0 4

3.2 1 5 3.9 4 4 3.15 0 0.5

3 2 0.5 3.64 0 2 3.4 0 1

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