Applied Statistics And Data Analysis For Public Health Assignment Sample

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Introduction of Applied Statistics And Data Analysis For Public Health Assignment 

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The solid way of life dataset was acquired from a speculative randomised monitoring preliminary which was directed to assess a way of life wellbeing training mediation. The intercession was conveyed for more than 12 weeks and the primary point was to advance solid ways of living among college understudies. A few explicit targets of the review were to increment wellbeing education and work on solid load among concentrate on members. Estimations for weight, wellbeing education and other important review factors were taken at benchmark and toward the finish of 12 weeks. In the table, a number of variables have been provided associated with the age of all the participants, their status of diabetes, their health condition and literacy, the percentage etc. Furthermore, the height of all the participants has been provided in the table along with their status of intervention and location. In the table, it also shows how many selected participants are female and how many are male or do they smoke or not. In this following report, an inspection will be made for whether there is huge contrast in wellbeing proficiency at gauge between members in campus A contrasted with members in campus B.

Question 1

Significant difference between campus A participants and campus B participants in health literacy at baseline

T-Test

Group Statistics

Location N Mean Std. Deviation Std. Error Mean

Health literacy at baseline Campus A 43 58.4105 15.78844 2.40771

Campus B 37 58.9045 14.57707 2.39646

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

Health literacy at baseline Equal variances assumed .646 .424 -.145 78 .885 -.49402 3.41769 -7.29811 6.31007

Equal variances not assumed -.145 77.593 .885 -.49402 3.39707 -7.25763 6.26959

In the above, a significant difference between the two variables has been formed with their statistical analysis and these variables are participants in both the campus A and B. through the hypothesis analysis it has been determined that a total of 80 participants has been involved among which 43 were in campus A and the rest 37 were on campus in B. The mean value for the members in campus A has been valued as 58.41 and that for campus B has been formed as 58.90. The standard deviation value for the members in campus A has been valued as 15.78 and that for campus B has been formed as 14.57. The standard error value for the members in campus A has been valued as 2.40 and that for campus B has been formed as 2.39.

The above independent sample test was carried out to evaluate any possible difference and relationship between health literacy and their location (Ott, 2018). Under the assumption of equal variances, the F, Sig, and t are valued as .646, .424 and -.145 respectively. The value of sigma 2 tailed assuming equal variances has been valued as 78 and the mean difference of it is determined as .885. The standard error, difference and its confidence interval is valued as -.49402, 3.41769 and -7.29811 respectively. However, by not assuming equal variances, the F, Sig and t are valued as -.145, 77.593 and .885 respectively. The value of sigma 2 tailed not assuming equal variances has been valued as -.49402 and the mean difference of it is determined as 3.36499. The standard error, difference and its confidence interval is valued as 3.3970, -7.25763 and 6.269598 respectively.

Question 2

Means

Case Processing Summary

Cases

Included Excluded Total

N Percent N Percent N Percent

Weight after intervention * Intervention 81 100.0% 0 0.0% 81 100.0%

Report

Weight after intervention

Intervention Mean N Std. Deviation

Control group 64.5660 47 12.62243

Intervention group 70.3429 34 16.57254

Total 66.9909 81 14.59915

A substantial difference has been generated between the two variables in the preceding statistical analysis, and these variables are individuals with weight after intervention in both the control and intervention groups. According to the hypothesis analysis, a total of 80 people were engaged, with 47 in the control group and the remaining 34 in the intervention group (Rahman, 2020). The mean value for participants of the control group was 64.5, whereas the mean value for members of the intervention group was 70.3. The participants of the control group had a standard deviation of 12.62, whereas those in the intervention group had a standard deviation of.35949. The standard error value for the members in the control group has been valued as .05249 and that for the intervention group has been formed as .06165.

Question 3

T-Test

Group Statistics

Intervention

N

Mean

Std. Deviation

Std. Error Mean

Asthma diagnosed

Control group

47

.1489

.35987

.05249

Intervention group

34

.1471

.35949

.06165

In the above, a significant difference between the two variables has been formed with their statistical analysis and these variables are participants with asthma in both the control and intervention group. Through the hypothesis analysis it has been determined that a total of 80 participants have been involved among which 47 were in the control group and the rest 34 were in the intervention group. The mean value for the members in campus A has been valued as 58.41 and that for campus B has been formed as 58.90. The standard deviation value for the members in campus A has been valued as 15.78 and that for campus B has been formed as 14.57. The standard error value for the members in campus A has been valued as 2.40 and that for campus B has been formed as 2.39.

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

Asthma diagnosed

Equal variances assumed

.002

.963

.023

79

.982

.00188

.08099

-.15932

.16308

Equal variances not assumed

.023

71.306

.982

.00188

.08097

-.15956

.16332

In the above, a significant difference between the two variables has been formed with their statistical analysis and these variables are participants with asthma in both the control and intervention group. Through the hypothesis analysis it has been determined that a total of 80 participants have been involved among which 47 were in the control group and the rest 34 were in the intervention group. The mean value for the members in the control group has been valued as .1489 and that for the intervention group has been formed as .1479. The standard deviation value for the members in the control group has been valued as .35987 and that for the intervention group has been formed as .35949. The standard error value for the members in the control group has been valued as .05249 and that for the intervention group has been formed as .06165.

Question 4

Means

Case Processing Summary

Cases

Included Excluded Total

N Percent N Percent N Percent

Health literacy at baseline * Age 81 100.0% 0 0.0% 81 100.0%

Report

Health literacy at baseline

Age Mean N Std. Deviation

18 57.1429 2 30.30458

19 60.6380 13 17.14940

20 56.4898 14 12.59211

21 59.5079 9 10.71836

22 68.6329 3 17.55278

23 50.0000 3 21.42857

24 54.4957 2 40.90512

25 59.5629 6 8.67671

26 47.6190 3 8.24786

27 64.3095 3 7.17860

28 57.1429 1 .

29 57.1429 2 10.10153

30 46.4295 6 12.57532

33 69.8600 2 9.27724

34 56.1429 2 1.41421

35 73.1238 3 20.93842

36 27.5600 1 .

39 56.1429 1 .

40 75.0000 2 25.25381

41 70.4000 1 .

42 64.2857 1 .

44 57.1429 1 .

Total 58.4441 81 15.15341

A significant difference has been formed between the participants of different age groups and in their health literacy at baseline above. Participants of age 18 had a mean value of 57.14 and N value of 2 with a standard deviation of 30.30. Participants of age 19 had a mean value of 60.63 and N value of 13 with a standard deviation of 17. Participants of age 20 had a mean value of 56.4898 and N value of 14 with a standard deviation of 12.59. Participants of age 21 had a mean value of 59.50 and N value of 9 with a standard deviation of 10.71. Participants of age 22 had a mean value of 68.63 and N value of 3 with a standard deviation of 17.55. Participants of age 23 had a mean value of 50 and N value of 3 with a standard deviation of 21.42. Participants of age 24 had a mean value of 59.56 and N value of 2 with a standard deviation of 40.9 (Bachner, 2021). Participants of age 25 had a mean value of 59.56 and N value of 6 with a standard deviation of 8.67. Participants of age 26 had a mean value of 57.14 and N value of 2 with a standard deviation of 30.30. Participants of age 27 had a mean value of 60.63 and N value of 13 with a standard deviation of 17. Participants of age 28 had a mean value of 56.4898 and N value of 14 with a standard deviation of 12.59. Participants of age 29 had a mean value of 59.50 and N value of 9 with a standard deviation of 10.71. Participants of age 30 had a mean value of 68.63 and N value of 3 with a standard deviation of 17.55. Participants of age 31 had a mean value of 50 and N value of 3 with a standard deviation of 21.42. Participants of age 32 had a mean value of 59.56 and N value of 2 with a standard deviation of 40.9. Participants of age 33 had a mean value of 59.56 and N value of 6 with a standard deviation of 8.67. Participants of age 34 had a mean value of 57.14 and N value of 2 with a standard deviation of 30.30. Participants of age 35 had a mean value of 73.12 and N value of 3 with a standard deviation of 20.93. Participants of age 36 had a mean value of 27.56 and N value of 1 and no standard deviation has been formed. Participants of age 37 had a mean value of 59.50 and N value of 9 with a standard deviation of 10.71. Participants of age 38 had a mean value of 68.63 and N value of 3 with a standard deviation of 17.55 (Wong et al. 2019). Participants of age 39 had a mean value of 56.14 and N value of 1 and no standard deviation has been formed. Participants of age 40 had a mean value of 59.56 and N value of 2 with a standard deviation of 40.9. Participants of age 41 had a mean value of 70.40 and N value of 1 and no standard deviation has been formed. Participants of age 42 had a mean value of 50 and N value of 3 and no standard deviation has been formed. Participants of age 43 had a mean value of 59.56 and N value of 2 and no standard deviation has been formed. A total of 81 participants has been formed with a mean value of 58.44 and N value of 81 with a standard deviation of 15.15.

Question 5

T-Test

Group Statistics

Intervention

N

Mean

Std. Deviation

Std. Error Mean

Health literacy at baseline

Control group

47

55.4680

14.53325

2.11989

Intervention group

34

62.5582

15.23789

2.61328

Sex

Control group

47

1.68

.471

.069

Intervention group

34

1.68

.475

.081

Age

Control group

47

24.38

6.395

.933

Intervention group

34

26.03

7.039

1.207

In the preceding statistical analysis, a significant difference was established between the two variables, which are persons with Health literacy at baseline in both the control and intervention groups. The hypothesis analysis revealed that a total of 80 persons were involved, with 47 in the control group and the remaining 34 in the intervention group. The mean value for control group participants was 55.46, whereas the mean value for intervention group participants was 62.55. The standard deviation for the control group was 14.53, whereas the standard deviation for the intervention group was 15.23 (Rahman, 2020). The members' average error value in the control group has been valued as 2.11 and that for the intervention group has been formed as 2.61.

In the above, a significant difference between the two variables has been formed with their statistical analysis and these variables are participants with their gender in both the control and intervention group. Through the hypothesis analysis it has been determined that a total of 80 participants have been involved among which 47 were in the control group and the rest 34 were in the intervention group. The mean value for the members in the control group has been valued as 1.68 and that for the intervention group has been formed as 1.68. The standard deviation value for the members in the control group has been valued as .471 and that for the intervention group has been formed as .475. The standard error value for the members in the control group has been valued as .069 and that for the intervention group has been formed as .081.

In the above, a significant difference between the two variables has been formed with their statistical analysis and these variables are participants with their age in both the control and intervention group (Benke and Benke, 2018). Through the hypothesis analysis it has been determined that a total of 80 participants have been involved among which 47 were in the control group and the rest 34 were in the intervention group. The mean value for the members in the control group has been valued as 24.38 and that for the intervention group has been formed as 26.03. The standard deviation value for the members in the control group has been valued as 6.395 and that for the intervention group has been formed as 7.039. The standard error value for the members in the control group has been valued as .933 and that for the intervention group has been formed as 1.207.

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

Health literacy at baseline

Equal variances assumed

.003

.957

-2.123

79

.037

-7.09024

3.33921

-13.73678

-.44370

Equal variances not assumed

-2.107

69.218

.039

-7.09024

3.36499

-13.80284

-.37765

Sex

Equal variances assumed

.007

.935

.041

79

.967

.004

.106

-.207

.216

Equal variances not assumed

.041

70.934

.967

.004

.107

-.208

.217

Age

Equal variances assumed

1.125

.292

-1.096

79

.276

-1.646

1.502

-4.636

1.343

Equal variances not assumed

-1.079

67.029

.284

-1.646

1.526

-4.691

1.399

Health literacy at baseline

In the above, the independent test of sample has been performed to determine any possible difference and relation between health literacy, participants with their gender, age. Under health literacy baseline, assuming equal variances, the F, Sig and t are valued as .003, .957 and -2.123 respectively. The value of sigma 2 tailed assuming equal variances has been valued as 79 and the mean difference of it is determined as 0.37. The standard error, difference and its confidence interval is valued as -7.09, 3.33 and -13.7 respectively. However, by not assuming equal variances, the F, Sig and t are valued as -2.107, 69.218 and .039 respectively. The value of sigma 2 tailed not assuming equal variances has been valued as -7.09024 and the mean difference of it is determined as 3.36499. The standard error, difference and its confidence interval is valued as -13.80284, 3.33 and -.37765 respectively.

Participants with gender

The above independent sample test was carried out to evaluate any possible difference and relationship between health literacy, participants with their gender, and age. Under the assumption of equal variances, the F, Sig, and t are valued as .007, .935 and .041 respectively. The value of sigma 2 tailed assuming equal variances has been valued as 79 and the mean difference of it is determined as .967. The standard error, difference and its confidence interval is valued as .004, .106 and -.207 respectively. However, by not assuming equal variances, the F, Sig and t are valued as .041, 70.934 and .967 respectively. The value of sigma 2 tailed not assuming equal variances has been valued as -7.09024 and the mean difference of it is determined as 3.36499. The standard error, difference and its confidence interval is valued as .004, .107 and -.208 respectively.

Participants with age

In the above, the independent test of sample has been performed to determine any possible difference and relation between health literacy, participants with their gender, age. Under health literacy baseline, assuming equal variances, the F, Sig and t are valued as 1.125, .292 and -1.096 respectively. The value of sigma 2 tailed assuming equal variances has been valued as 79 and the mean difference of it is determined as .276. The standard error, difference and its confidence interval is valued as .276, -1.646 and 1.502 respectively. However, by not assuming equal variances, the F, Sig and t are valued as -1.079, 67.029 and .284 respectively. The value of sigma 2 tailed not assuming equal variances has been valued as -7.09024 and the mean difference of it is determined as -1.646. The standard error, difference and its confidence interval is valued as 1.526, -4.691 and 1.399 respectively.

Conclusion

In this following statistical report of public health, some essential and statistical differences have been formed in the data. The difference between participants in both the campus A and B has been determined in this report with their health literacy. Also, the intervention of participants body mass before and after the intervention has been provided through the statistical report. Furthermore, considering the age and gender of the participants, post intervention has been forecasted. In this following factual report of general wellbeing, a few fundamental and measurable contrasts have been shaped in the information. The distinction between members in both the grounds A and B not entirely set in stone in that frame of mind with their wellbeing education. Likewise, the mediation of members weight when the intercession has been given through the measurable report. Moreover, considering the age and orientation of the members, post intercession has been anticipated.

Reference list

Journals

Bachner, J., 2021. Pedagogical Recommendations for Applied Statistics Courses. In The Palgrave Handbook of Political Research Pedagogy (pp. 311-321). Palgrave Macmillan, Cham.

Baek, H., Cho, M., Kim, S., Hwang, H., Song, M. and Yoo, S., 2018. Analysis of length of hospital stay using electronic health records: A statistical and data mining approach. PloS one13(4), p.e0195901.

Bahariniya, S. and Madadizadeh, F., 2021. Review of the Statistical Methods Used in Original Articles Published in Iranian Journal of Public Health from 2015–2019: A Review Article. Iranian Journal of Public Health50(8), p.1577.

Benke, K. and Benke, G., 2018. Artificial intelligence and big data in public health. International journal of environmental research and public health15(12), p.2796.

Berman, A., 2018, November. General topics in applied public health statistics. In APHA's 2018 Annual Meeting & Expo (Nov. 10-Nov. 14). APHA.

Chen, X.W., 2022. Public health. In Network Science Models for Data Analytics Automation (pp. 35-47). Springer, Cham.

Escolà-Gascón, Á., 2022. Statistical indicators of compliance with anti-COVID-19 public health measures at European airports. International Journal of Disaster Risk Reduction68, p.102720.

Hernán, M.A., Hsu, J. and Healy, B., 2019. A second chance to get causal inference right: a classification of data science tasks. Chance32(1), pp.42-49.

McClure, E.S., Vasudevan, P., Bailey, Z., Patel, S. and Robinson, W.R., 2020. Racial capitalism within public health—how occupational settings drive COVID-19 disparities. American journal of epidemiology189(11), pp.1244-1253.

Mooney, S.J. and Pejaver, V., 2018. Big data in public health: terminology, machine learning, and privacy. Annual review of public health39, pp.95-112.

Ott, W.R., 2018. Environmental statistics and data analysis. Routledge.

Peng, L., 2018, November. Invited Session in Applied Public Health Statistics. In APHA's 2018 Annual Meeting & Expo (Nov. 10-Nov. 14). APHA.

Rahman, A. ed., 2020. Statistics for data science and policy analysis. Springer Nature.

Rahman, A. ed., 2020. Statistics for data science and policy analysis. Springer Nature.

Saglimbene, V., Strippoli, G., Craig, J.C. and Wong, G., 2020. Statistics and data analyses—a new educational series for nephrologists. Kidney International97(2), pp.233-235.

Vinceti, S.R. and Filippini, T., 2021. Towards the dismissal of null hypothesis/statistical significance testing in public health, public law and toxicology.

Wing, C., Simon, K. and Bello-Gomez, R.A., 2018. Designing difference in difference studies: best practices for public health policy research. Annual review of public health39.

Wong, Z.S., Zhou, J. and Zhang, Q., 2019. Artificial intelligence for infectious disease big data analytics. Infection, disease & health24(1), pp.44-48.

Wong, Z.S., Zhou, J. and Zhang, Q., 2019. Artificial intelligence for infectious disease big data analytics. Infection, disease & health24(1), pp.44-48.

Zhao, Y. and Chen, D.G. eds., 2021. Modern Statistical Methods for Health Research. Springer.

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