• Internal Code :
  • Subject Code :
  • University :
  • Subject Name : Statistics

Data Analysis and Research Design - Question 1

As a practicing health professional you are quite concerned about the lack of sun smart behavior among your community members; you have even heard some people boasting about not using sunscreen and proudly showing off their sun burns. You are quite aware of the beneficial effects of sunscreen and would like to conduct your own research project to demonstrate to others the benefits of using sun screen in terms of prevention and reduction of the cases of melanoma. It has been few years since you passed EPID1000 and are a bit rusty on different study designs so you immediately email your ex-unit coordinator to send you all the materials (especially lecture recordings and tutorial notes) but you don’t get any reply. Eventually,on an old USB you found everything.

Please give us a short description of how each design can be used to demonstrate the benefits of using sun screen. You should use the points provided in the review exercise (tutorial 11) to cover all the features of each design.

a) Cross-sectional study.

b) Prospective Cohort study.

c) Retrospective Cohort study.

d) Case Control study.

e) Quasi-experimental study.

f) Randomized controlled trial

(No need to worry about the ethics for e and f parts); this is a hypothetical exercise to assess your understanding of different study designs).

Note: Please be specific about the specified exposure and outcome given for this question. No marks for writing general design features from the lectures. We want you to ‘apply’ your knowledge of study designs in light of the given scenario.

Formatting &Line limit Requirements:For each of the six parts please use Times New Roman size 12 font, normal page borders and 10 lines maximum for each part,(10 lines DONOT mean ten sentences or ten statements). These formatting requirements are for Q1 ONLY, rest of the questions are free from any formatting requirements.

For Q2, Q3, Q4, Q5, Q6, Q7 and Q8you will conduct ALL analyses using your own random sample of 50(Video & instructions posted separately).

NO MARKS will be awarded:

  • If you used the entire dataset(N=700) instead of your own sample of 50.

  • If you do not provide the relevant SPSS output for all questions.NO SPSS Output = No Mark

You can choose a different sample of 50 for every question or use the same sample of 50 for all questions; it is up to you (Please read FAQs for more questions).

Data Analysis and Research Design - Question 2

Write null and a non-directional alternative hypotheses that can be tested with anIndependent Samples t test. Briefly describe, and report on the assumption at the analysis stage.Provide complete interpretation of your results including their statistical and practical significance.

H0: population means of resting energy expenditure are equal for male and female

H1: population means of resting energy expenditure are not equal for male and female

The hypothesis can be testing using an independent sample t test.

Group Statistics

 

Gender

N

Mean

Std. Deviation

Std. Error Mean

Resting Energy Expenditure

Males

31

1370.35

350.910

63.025

Females

19

1268.58

279.237

64.061

 

Independent Samples Test

 

 

Levene's Test for Equality of Variances

t-test for Equality of Means

 

 

F

Sig.

t

df

Sig. (2-tailed)

Mean Difference

Std. Error Difference

95% Confidence Interval of the Difference

 

 

Lower

Upper

Resting Energy Expenditure

Equal variances assumed

.979

.327

1.072

48

.289

101.776

94.949

-89.133

292.684

Equal variances not assumed

 

 

1.133

44.624

.263

101.776

89.867

-79.267

282.819

The assumption of normality has been met for male population. However, normality is slightly deviated for female population. The p-value of the F test suggests that the assumption of equality of variances has been met.

The p-value of the independent sample t-test is 0.289. As the p-value is greater than the level of significance 0.05, we can accept the null hypothesis. This concludes that there is no such evidence of significant difference in population means of resting energy expenditure between male and female populations.

Data Analysis and Research Design - Question 3

a) Are people more willing to help strangers who ask for money than those who ask for a cigarette?

Choose a suitable test to answer this question and provide a short description of your data analysis including statistical significance of your findings. No need to list or test any assumptions

H0: population proportion of peoples willing to help strangers ask for money equal to population proportion of peoples willing to help strangers ask for a cigarette

H1: population proportion of peoples willing to help strangers ask for money is greater than population proportion of peoples willing to help strangers ask for a cigarette

Stranger help (Money)

 

 

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Definitely not

5

10.0

10.0

10.0

Probably Not

2

4.0

4.0

14.0

Possibly yes

24

48.0

48.0

62.0

Definitely yes

19

38.0

38.0

100.0

Total

50

100.0

100.0

 

 

Stranger help (Cigarettes)

 

 

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Definitely Not

36

72.0

72.0

72.0

Probably Not

6

12.0

12.0

84.0

Possibly Yes

4

8.0

8.0

92.0

Definitely Yes

4

8.0

8.0

100.0

Total

50

100.0

100.0

 

The two population proportion test is suitable for this problem.

The two proportions:

p1 = 43/50 = 0.86

p2 = 8/50 = 0.16

The overall sample proportion: p = (43 + 8) / (50 + 50) = 0.51.

The test statistic formula:

Z = (p1 – p2)/Ö{(p(1-p))(1/n1+1/n2)}

 = (0.86 – 0.16)/Ö{(0.51(1-0.53))(1/50+1/50)}

= 9.81

p-value = 0.000

The p-value of the two sample proportion test is 0.000. As the p-value is less than the level of significance 0.05, we can reject the null hypothesis. Therefore, we can conclude that people are more willing to help strangers who ask for money than those who ask for a cigarette.

b) Are females more willing than males to help strangers when they ask for money?

Choose a suitable test to answer this question and provide a short description of your data analysis including statistical significance of your findings. No need to list or test any assumptions

H0: population proportion of females willing to help strangers ask for money equal to population proportion of males willing to help strangers ask for money 

H1: population proportion of female willing to help strangers ask for money is greater than population proportion of males willing to help strangers ask for money

Stranger help (Money) * Gender Crosstabulation

Count

 

 

 

 

 

 

Gender

Total

 

 

Males

Females

Stranger help (Money)

Definitely not

5

0

5

Probably Not

2

0

2

Possibly yes

14

10

24

Definitely yes

10

9

19

Total

31

19

50

The two population proportion test is suitable for this problem.

The two proportions:

p1 = 19/19 = 1.00

p2 = 24/31 = 0.61

The overall sample proportion: p = (19 + 24 / (19 + 31) = 0.86.

The test statistic formula:

Z = (p1 – p2)/Ö{(p(1-p))(1/n1+1/n2)}

 = (0.1.00 – 0.61)/Ö{(0.86(1-0.86))(1/19+1/31)}

= 3.01

p-value = 0.003

The p-value of the two sample proportion test is 0.003. As the p-value is less than the level of significance 0.05, we can reject the null hypothesis. Therefore, we can conclude that females are more willing than males to help strangers when they ask for money.

Data Analysis and Research Design - Question 4

Choose only those who are27 years and younger and test the hypothesis that they come from a population in which mean exercise time is 6 hours per week.

Write null and alternative hypotheses.

Choose a suitable test and carry out the appropriate analyses and write a short summary of your results including their statistical significance No need to list or test any assumptions.

H0: population mean exercise time is 6 hours per week

H1: population mean exercise time is different from 6 hours per week

A one sample t test wtll be suitable to answer this question.

One-Sample Test

 

Test Value = 6

 

t

df

Sig. (2-tailed)

Mean Difference

95% Confidence Interval of the Difference

 

Lower

Upper

Exercise hours per week

-.419

23

.679

-.124

-.74

.49

The p-value of the one sample t test is 0.679 which is greater than the level of significance 0.05. We can accept the null hypothesis. Therefore, we can conclude that those who are 27 years and younger have mean exercise time of 6 hours per week.

Data Analysis and Research Design - Question 5

Is there any significant difference in the Academic performance between those who Strongly Agree, Agree, Disagree and Strongly Disagree to the statement It is great not to have an invigilated final exam?

Choose a suitable test to answer this question. Carry out the appropriate analyses and write a short summary of your results and conclusion.Report on the assumption at the analysis stage.

H0: Population means of academic performance between those who Strongly Agree, Agree, Disagree and Strongly Disagree are equal

H1: Population means of academic performance between those who Strongly Agree, Agree, Disagree and Strongly Disagree are different for at least one

A one way ANOVA is suitable to answer this question.

Test of Homogeneity of Variances

Academic Performance University

 

Levene Statistic

df1

df2

Sig.

12.406

3

46

.000

 

ANOVA

Academic Performance University

 

 

 

 

 

Sum of Squares

df

Mean Square

F

Sig.

Between Groups

23.712

3

7.904

11.373

.000

Within Groups

31.968

46

.695

 

 

Total

55.680

49

 

 

 

The histogram with normal curve suggests that the assumption of normality is violated in this case. Also the assumption of equality of variances has not been met as the p-value of the Levene Statistic is less than the level of significance 0.05.

The p-value of the ANOVA test is 0.000. This suggests that we can reject the null hypothesis at 5% level of significance. Therefore, we can conclude that there is significant difference in the Academic performance between those who Strongly Agree, Agree, Disagree and Strongly Disagree to the statement It is great not to have an invigilated final exam?

Data Analysis and Research Design - Question 6

Is there any significant difference in text messaging behavior while driving among people with different blood groups?

Choose a suitable test to answer this question. Carry out the appropriate analyses and write a short summary of your results and conclusion.No need to list or test any assumptions

H0: Population means of test massaging behavior while driving among people with different blood groups are equal

H1: Population means of test massaging behavior while driving among people with different blood groups are different for at least one

A one way ANOVA is suitable to answer this question.

Test of Homogeneity of Variances

Texts while Driving

 

 

Levene Statistic

df1

df2

Sig.

2.975

3

46

.041

 

ANOVA

Texts while Driving

 

 

 

 

 

Sum of Squares

df

Mean Square

F

Sig.

Between Groups

1.768

3

.589

.484

.695

Within Groups

56.012

46

1.218

 

 

Total

57.780

49

 

 

 

The histogram with normal curve depicts the violation of assumption of normality. Also the assumption of equality of variances has not been met as the p-value of the Levene Statistic is less than the level of significance 0.05.

The p-value of the ANOVA test is 0.695. As this p-value is greater than 0.05, the level of significance, this suggests that we can accept the null hypothesis at 5% level of significance. Therefore, we can conclude that there is no significant difference in text messaging behavior while driving among people with different blood groups.

Data Analysis and Research Design - Question 7

Is there any significant difference in academic achievement at school (based on ATAR score School) and later at university (based on Academic Performance Uni score)?

Choose a suitable test to answer this question. Carry out the appropriate analyses and write a short summary of your results and conclusion.No need to list or test any assumptions

H0: Population means of academic achievement at school and academic achievement at university groups are equal

H1: Population means of academic achievement at school and academic achievement at university groups are different

An independent sample t test is suitable to answer this question.

Independent Samples Test

 

 

Levene's Test for Equality of Variances

t-test for Equality of Means

 

 

F

Sig.

t

df

Sig. (2-tailed)

Mean Difference

Std. Error Difference

95% Confidence Interval of the Difference

 

 

Lower

Upper

Academic_performance

Equal variances assumed

132.009

.000

11.740

98

.000

3.880

.330

3.224

4.536

Equal variances not assumed

 

 

11.740

73.086

.000

3.880

.330

3.221

4.539

The histogram with normal curve shows assumption of normality holds for academic performance at University. However, a non-normal behaviour has been seen for academic performance at school. Also the assumption of equality of variances has not been met as the p-value of the F Statistic is less than the level of significance 0.05.

The p-value of the independent sample t test is 0.000. As this p-value is less than 0.05, the level of significance, this suggests that we can reject the null hypothesis at 5% level of significance. Therefore, we can conclude that there is significant difference in academic achievement at school (based on ATAR score School) and later at university (based on Academic Performance Uni score).

Data Analysis and Research Design - Question 8

Participants were asked to name one positive aspect, if possible, about COVID-19 experience. (Variable Corona_Positives). Unexpectedly all participants had at least one positive aspect to report. You will see that top five responses have been coded as A, B, C, D and Ebut no labels or descriptions. Use your discretion (and creativity or personal experience) to assign each code a hypothetical response or description, make up any whatever you think these are/can/or should be, and provide a suitable graph showing labels/description of these five responses.

A = Environment

B = Better Hygiene

C= Innovation of connectedness

D = Peace

E = Digitized Education

(Relevant SPSS output not provided with your written answer = No mark).

This applies to Qs2-8

‘FAQs’ posted will be extremely useful so please refer to it before you ask any question.

Thank you everyone for posting your questions on the Discussion Board or taking them to Open Collaborate sessionslast time. Same rules apply to this assignment.

No emails,otherwise it will not be fair to others.

Remember, at the center of any academic work, lies clarity and evidence. Should you need further assistance, do look up to our Statistics Assignment Help

Get It Done! Today

Applicable Time Zone is AEST [Sydney, NSW] (GMT+11)
Not Specific >5000
  • 1,212,718Orders

  • 4.9/5Rating

  • 5,063Experts

Highlights

  • 21 Step Quality Check
  • 2000+ Ph.D Experts
  • Live Expert Sessions
  • Dedicated App
  • Earn while you Learn with us
  • Confidentiality Agreement
  • Money Back Guarantee
  • Customer Feedback

Just Pay for your Assignment

  • Turnitin Report

    $10.00
  • Proofreading and Editing

    $9.00Per Page
  • Consultation with Expert

    $35.00Per Hour
  • Live Session 1-on-1

    $40.00Per 30 min.
  • Quality Check

    $25.00
  • Total

    Free
  • Let's Start

Get
500 Words Free
on your assignment today

Browse across 1 Million Assignment Samples for Free

Explore MASS
Order Now

Request Callback

My Assignment Services- Whatsapp Tap to ChatGet instant assignment help

Hire Certified Experts
Ask your Question
Need Assistance on your
existing assignment order?

We care

MyAssignmentServices uses cookies to deliver the best experience possible.
My Assignment Services acknowledges the academic integrity guidelines prescribed as per Australian Universities to ensure that the services, sample material, and study resources available on our website, in no way are utilised to commit academic misconduct of any type. All users of our services must adhere to and affirm acceptance of all conditions elucidated in our policy document on academic integrity.

Please accept and affirm the following to be able to continue exploring our website and services: I agree to NOT use any educational material, study resources, assignment samples, online mentoring services, available on the web domain www.myassignmentservices.com and all its subdomains to commit any academic misconduct. I have read and been made fully aware of the academic integrity policy of My Assignment Services and by clicking on the button below, I am in principle, wilfully and legally bound to adhere to guidelines of the academic integrity policy in whole and in part.
View Cookies policy | How we ensure Academic Integrity?