Statistics for business decisions

Data is given…you have to make graphs chats or solve questions Other questions is some sort of other data given I will upload to writer..for that spreadsheet you have to do histogram And show mean, standard deviation,correction etc. Some other calculations
Instruction:
Please make graphs correctly by taking correct data
Solve questions where asked
All answers should be done

FACULTY OF HIGHER EDUCATION

Due Friday 5pm week 11

WORTH 30%

Task 1 10 Marks

Consumer Research, Inc., is an independent agency that conducts research on consumer attitudes and behaviours for a variety of firms. In one study, a client asked for an investigation of consumer characteristics that can be used to predict the amount charged by credit card users. Data were collected on annual income, household size, and annual credit card charges for a sample of 50 consumers. The following data are recorded for Consumer information.

Income ($1000s)

Household Size

Amount Charged ($)

Income ($1000s)

Household Size

Amount Charged ($)

54

3

4016

54

6

5573

30

2

3159

30

1

2583

32

4

5100

48

2

3866

50

5

4742

34

5

3586

31

2

1864

67

4

5037

55

2

4070

50

2

3605

37

1

2731

67

5

5345

40

2

3348

55

6

5370

66

4

4764

52

2

3890

51

3

4110

62

3

4705

25

3

4208

64

2

4157

48

4

4219

22

3

3579

27

1

2477

29

4

3890

33

2

2514

39

2

2972

65

3

4214

35

1

3121

63

4

4965

39

4

4183

42

6

4412

54

3

3720

21

2

2448

23

6

4127

44

1

2995

27

2

2921

37

5

4171

26

7

4603

62

6

5678

61

2

4273

21

3

3623

30

2

3067

55

7

5301

22

4

3074

42

2

3020

46

5

4820

41

7

4828

66

4

5149

Required:

Use methods of descriptive statistics to summarize the data. Comment on the findings.
Develop estimated regression equations, first using annual income as the in- dependent variable and then using household size as the independent variable. Which variable is the better predictor of annual credit card charges? Discuss your findings.
Develop an estimated regression equation with annual income and household size as the independent variables. Discuss your findings.
What is the predicted annual credit card charge for a three-person household with an annual income of $40,000?
Discuss the need for other independent variables that could be added to the model. What additional variables might be helpful?

Task 2 10 Marks

The data set for group assignment you can find on Blackboard in the folder assignment. In the other doc upload you find data to solve this question .

Required:

Activity 01:

Enter all data from the spreadsheet “Data for Assignment “into Excel. You will need to set up the variable view with the following 11 variables and then enter the data in excel:

Student_ID,
Year_Enrolled,
HI001_Final_Exam,
HI001_Assignment_01,
HI001_Assignment_02,
HI002_Final_Exam,
HI002_Assignment_01,
HI002_Assignment_02,
HI003_Final_Exam,
HI003_Assignment_01,

Activity 02:

Draw a histogram for each one of the 11 variables?

Do descriptive statistics (mean, standard deviation, minimum, maximum) for each one of the 11 variables.

Activity 03:

Do at least 10 different correlations between the any pairs of variables: For example:
HI001_Final_Exam and HI002_Final_Exam
HI001_Assignment_01 and HI001_Assignment_02

For each correlation discuss the results:
Are they are positive/negatively correlated?
Are they weak or strong correlations?
What is the significance value?
What does the significance value reveal about the data we have used?

Required:

Copy –paste the result from your Excel file to a Word document.
Copy-paste ALL the output from all the activities requested in Activity 01 to 03 in Excel and put the answers in the same Word document.
Answer all discussion questions requested in Activity 01 to 03 and put the answers in the same Word document.
Submit a soft copy of the Excel files used in Excel and the Assignment Word document online under Assignment final submission.

Task 3 10 Marks

As part of a long-term study of individuals 65 years of age or older, sociologists and physicians at the Wentworth medical Center in upstate New York investigated the relationship between geographic location and depression. A sample of 60 individuals, all in reasonably good health, was selected; 20 individuals were residents of Florida, 20 were residents of New York, and 20 were residents of North Carolina. Each of the individuals sampled was given a standardized test to measure depression. The data collected follow; higher test scores indicate higher levels of depression. These data are available on the website that accompanies this text in the file named medical1. A second part of the study considered the relationship between geographic location and depression for individuals 65 years of age or older who had a chronic health condition such as arthritis, hypertension, and/or heart ailment. A sample of 60 individuals with such conditions was identified. Again, 20 were residents of Florida, 20 were residents of New York, and 20 were residents of North Carolina. The levels of depression recorded for this study follow. These data are available on the website that accompanies this text in the file named medical2.

Florida

New York

North Carolina

Florida

New York

North Carolina

3

8

10

13

14

10

7

11

7

12

9

12

7

9

3

17

15

15

3

7

5

17

12

18

8

8

11

20

16

12

8

7

8

21

24

14

8

8

4

16

18

17

5

4

3

14

14

8

5

13

7

13

15

14

2

10

8

17

17

16

6

6

8

12

20

18

2

8

7

9

11

17

6

12

3

12

23

19

6

8

9

15

19

15

9

6

8

16

17

13

7

8

12

15

14

14

5

5

6

13

9

11

4

7

3

10

14

12

7

7

8

11

13

13

3

8

11

17

11

11

Required:

Use descriptive statistics to summarize the data from the two studies. What are your preliminary observations about the depression scores?
Use analysis of variance on both data sets. State the hypotheses being tested in each case. What are your conclusions?
Use inferences about individual treatment means where appropriate. What are your conclusions?
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