### Avail The Best PUBH620 MJA Manuscript Assignment Help By Online Tutors At Low Prices!!

Home   Course
Previous << || >> Next

ARE YOU LOOKING FOR RELIABLE PUBH620 MJA MANUSCRIPT ASSIGNMENT HELP SERVICES? EXPERTSMINDS.COM IS RIGHT CHOICE AS YOUR STUDY PARTNER!

PUBH620 Biostatistics - Australian Catholic University

Learning Outcome 1: Distinguish between different statistical tests, especially in terms of application and interpretation.

Learning Outcome 2: Develop a sound statistical approach to the analysis and interpretation of public health data and communicate findings in an academic-standard output.

Learning Outcome 3: Critique public health research on the basis of its statistical methods, analysis and interpretation.

WORK TOGETHER WITH EXPERTSMIND'S TUTOR TO ACHIEVE SUCCESS IN PUBH620 MJA MANUSCRIPT ASSIGNMENT!

Question:

Purpose - To further develop students' analytical capabilities and ability to articulate their analysis in a form commonly encountered in practice: an academic journal article.

Present your results for your chosen OPTION ROAD TRAFFIC ACCIDENTS OR OPTION 2 DEPRESSION AND OBESITY in the format of a manuscript suitable for submission to the Medical Journal of Australia.

DO WANT TO HIRE TUTOR FOR ORIGINAL PUBH620 MJA MANUSCRIPT ASSIGNMENT SOLUTION? AVAIL QUALITY PUBH620 MJA MANUSCRIPT ASSIGNMENT WRITING SERVICE AT BEST RATES!

Assessment Task 1: Analysis of dataset

Descriptive statistics deals with the collection and presentation of data in the form of tables, graphs and diagrams. In addition, the findings like averages and other statistical measures were also included in the descriptive statistics

Inferential statistics covers hypothesis testing procedures and it is basically used for analysis of data and drawing conclusions with the available information from the sample data. The reliability analysis was also used in this section to validate the data taken into consideration

This study mainly focuses on the use of statistics and its various applications on various fields. Hypothesis testing procedure was mainly used to analyze and interpret the data. In various heath fields too statistics was widely used. In descriptive statistics, mean, median and mode are considered as the best measures of central tendency. Median is the appropriate measure of central tendency as it is not affected by outliers or extreme values. When the population from which the sample is taken is normally distributed, then mean is the appropriate measures of central tendency. When the distribution is skewed, then, the standard deviation could not be considered as the appropriate measure of central tendency. In such situations inter quartile range can be used as an appropriate measure of central tendency. Parametric tests also was not appropriate when the distribution is skewed and non parametric test was used as an alternate option whenever the distribution fails to validate the normality assumption

For the variables that are qualitative, we construct frequency distribution and pie charts, for the quantitative variables, descriptive statistics and histogram was constructed

SAVE YOUR HIGHER GRADE WITH ACQUIRING PUBH620 MJA MANUSCRIPT ASSIGNMENT HELP & QUALITY HOMEWORK WRITING SERVICES OF EXPERTSMINDS.COM

1.

a.

 Descriptives Statistic Std. Error AGE Mean 20.50 .025 95% Confidence Interval for Mean Lower Bound 20.45 Upper Bound 20.55 5% Trimmed Mean 19.77 Median 19.00 Variance 23.893 Std. Deviation 4.888 Minimum 16 Maximum 59 Range 43 Interquartile Range 3 Skewness 3.339 .012 Kurtosis 14.795 .025

The mean age is \$ 20.5 ± 4.89 and the median age is 19. The recorded minimum and maximum age of the respondents is 16 years and 59 years respectively. Here, we see that the mean age is greater than the median age, indicating that the distribution of age is skewed right. Thus, the assumption of age distribution follows normal distribution is violated in this case

b.

 Age Category Frequency Percent Valid Percent Cumulative Percent Aged 18 years at time of enrolment 17760 45.9 45.9 45.9 Aged 19 to 21 at time of enrolment 11672 30.2 30.2 76.1 Aged 22 to 25 at time of enrolment 5494 14.2 14.2 90.3 Aged 26 or more at time of enrolment 3755 9.7 9.7 100.0 Total 38681 100.0 100.0

Regarding the age at the time of enrolment, about 45.9% of the respondents enrolled at the age of 18 years, 30.2% of the respondents enrolled at the age between 19 years and 21 years, 14.2% of the respondents enrolled at the age between 22 years and 25 years and between 9.7% of the respondents enrolled after 25 years of age

GET GUARANTEED SATISFACTION OR MONEY BACK UNDER PUBH620 MJA MANUSCRIPT ASSIGNMENT HELP SERVICES OF EXPERTSMINDS.COM - ORDER TODAY NEW COPY OF THIS ASSIGNMENT!

2.

 STATE Frequency Percent Valid Percent Cumulative Percent NSW 15860 41.0 41.0 41.0 Victoria 13571 35.1 35.1 76.1 Queensland 7528 19.5 19.5 95.5 ACT 1722 4.5 4.5 100.0 Total 38681 100.0 100.0

Regarding the state, about 41% of the respondents enrolled were from NSW and 35.1% of the respondents enrolled were from Victoria

 GENDER Frequency Percent Valid Percent Cumulative Percent Male 10449 27.0 27.0 27.0 Female 28232 73.0 73.0 100.0 Total 38681 100.0 100.0

About 27% of the respondents included in this study are males and 73% of them are females, indicating that the study was dominated by female counterparts

 LIVING_ARRANGE Frequency Percent Valid Percent Cumulative Percent At home 20840 53.9 53.9 53.9 College/student accom 6850 17.7 17.7 71.6 Independently 10991 28.4 28.4 100.0 Total 38681 100.0 100.0

About 53.9% of the respondents who enrolled in this study said that they are living in their home, 17.7% of the respondents uses college accommodation facilities and 28.4% of the respondents said that they are living independently

 FACULTY Frequency Percent Valid Percent Cumulative Percent Arts and Sciences 9004 23.3 23.3 23.3 Education 15038 38.9 38.9 62.2 Health Sciences 11729 30.3 30.3 92.5 Theology and Philosophy 588 1.5 1.5 94.0 Business 2322 6.0 6.0 100.0 Total 38681 100.0 100.0

 DEGREE_TYPE Frequency Percent Valid Percent Cumulative Percent Single 34620 89.5 89.5 89.5 Double 4061 10.5 10.5 100.0 Total 38681 100.0 100.0

 METRO Frequency Percent Valid Percent Cumulative Percent Metro 27223 70.4 84.4 84.4 Non-metro 5015 13.0 15.6 100.0 Total 32238 83.3 100.0 Missing System 6443 16.7 Total 38681 100.0

 STUDY_MODE Frequency Percent Valid Percent Cumulative Percent FT 34770 89.9 89.9 89.9 PT 3911 10.1 10.1 100.0 Total 38681 100.0 100.0

 FEE_STATUS Frequency Percent Valid Percent Cumulative Percent Domestic 32238 83.3 83.3 83.3 International 6443 16.7 16.7 100.0 Total 38681 100.0 100.0

 dist_driving Frequency Percent Valid Percent Cumulative Percent Valid Less than 10 km a week 14601 37.7 37.7 37.7 More than 10 km a week 24080 62.3 62.3 100.0 Total 38681 100.0 100.0

 RTA_one_crash Frequency Percent Valid Percent Cumulative Percent Valid No RTAs 33628 86.9 86.9 86.9 One RTA or more 5053 13.1 13.1 100.0 Total 38681 100.0 100.0

 BL_owob Frequency Percent Valid Percent Cumulative Percent Valid Normal weight or underweight 14601 37.7 37.7 37.7 Overweight or obese 24080 62.3 62.3 100.0 Total 38681 100.0 100.0

 owob_par Frequency Percent Valid Percent Cumulative Percent Valid No obese parents 14455 37.4 37.4 37.4 At least one obese parent 24226 62.6 62.6 100.0 Total 38681 100.0 100.0

 depression Frequency Percent Valid Percent Cumulative Percent Valid Not depressed 34720 89.8 89.8 89.8 Depressed 3961 10.2 10.2 100.0 Total 38681 100.0 100.0

 OB Frequency Percent Valid Percent Cumulative Percent Valid Not obese 33628 86.9 86.9 86.9 Obese 5053 13.1 13.1 100.0 Total 38681 100.0 100.0

 edu_par Frequency Percent Valid Percent Cumulative Percent .00 16826 43.5 43.5 43.5 1.00 12918 33.4 33.4 76.9 2.00 8937 23.1 23.1 100.0 Total 38681 100.0 100.0

 Descriptives Statistic Std. Error driver_agg Mean 7.52 .022 95% Confidence Interval for Mean Lower Bound 7.47 Upper Bound 7.56 5% Trimmed Mean 7.52 Median 8.00 Variance 18.868 Std. Deviation 4.344 Minimum 0 Maximum 15 Range 15 Interquartile Range 7 Skewness -.004 .012 Kurtosis -1.173 .025 thrill Mean 5.00 .006 95% Confidence Interval for Mean Lower Bound 4.99 Upper Bound 5.01 5% Trimmed Mean 5.00 Median 5.00 Variance 1.497 Std. Deviation 1.224 Minimum 3 Maximum 7 Range 4 Interquartile Range 2 Skewness -.004 .012 Kurtosis -.998 .025 risk_accep Mean 8.53 .022 95% Confidence Interval for Mean Lower Bound 8.49 Upper Bound 8.57 5% Trimmed Mean 8.53 Median 9.00 Variance 18.985 Std. Deviation 4.357 Minimum 1 Maximum 16 Range 15 Interquartile Range 7 Skewness -.006 .012 Kurtosis -1.188 .025

Aggression Scores

The mean aggression score of drivers is 7.52 ± 4.34 with a median value of 8 and the recorded minimum and maximum aggression score of driver is 0 and 15 respectively. The mean score for thrill seeking behaviours is 5 ± 1.224 with a median value of 5 and the recorded minimum and maximum score for thrill seeking behaviour is 3 and 7 respectively. The mean score of risk acceptance behaviours is 8.53 ± 4.36 with a median value of 9 and the recorded minimum and maximum score of risk acceptance behaviour is 1 and 16 respectively.

EXPERTSMINDS.COM ACCEPTS INSTANT AND SHORT DEADLINES ORDER FOR PUBH620 MJA MANUSCRIPT ASSIGNMENT - ORDER TODAY FOR EXCELLENCE!

3.

Test Used: Independent Sample t test

Independent Variable: Gender

Dependent Variables: Driver Aggression Score, Thrill Score and Risk Acceptance Score

 Group Statistics GENDER N Mean Std. Deviation Std. Error Mean driver_agg Male 10449 7.52 4.335 .042 Female 28232 7.51 4.347 .026 thrill Male 10449 5.00 1.217 .012 Female 28232 5.00 1.226 .007 risk_accep Male 10449 8.59 4.358 .043 Female 28232 8.51 4.357 .026

 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 driver_agg Equal variances assumed .117 .732 .083 38679 .934 .004 .050 -.093 .102 Equal variances not assumed .083 18712.803 .934 .004 .050 -.093 .102 thrill Equal variances assumed .847 .357 -.370 38679 .711 -.005 .014 -.033 .022 Equal variances not assumed -.371 18783.250 .710 -.005 .014 -.033 .022 risk_accep Equal variances assumed .054 .817 1.571 38679 .116 .078 .050 -.019 .176 Equal variances not assumed 1.571 18663.180 .116 .078 .050 -.019 .176

From the above output, we see that

• There is no significant difference in scoring the driver aggression between male and female counterparts (p - value = 0.934 > 0.05)
• There is no significant difference in scoring the thrill seeking behaviour between male and female counterparts (p - value = 0.711 > 0.05)
• There is no significant difference in scoring the risk acceptance between male and female counterparts (p - value = 0.116 > 0.05)

Test Used: Independent Sample t test

Independent Variable: Metro

Dependent Variables: Driver Aggression Score, Thrill Score and Risk Acceptance Score

 Group Statistics METRO N Mean Std. Deviation Std. Error Mean driver_agg Metro 27223 7.53 4.345 .026 Non-metro 5015 7.49 4.303 .061 thrill Metro 27223 5.01 1.224 .007 Non-metro 5015 4.99 1.207 .017 risk_accep Metro 27223 8.53 4.358 .026 Non-metro 5015 8.59 4.304 .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 driver_agg Equal variances assumed 1.060 .303 .714 32236 .475 .048 .067 -.083 .178 Equal variances not assumed .719 7029.087 .472 .048 .066 -.082 .177 thrill Equal variances assumed 1.845 .174 .686 32236 .493 .013 .019 -.024 .050 Equal variances not assumed .692 7048.178 .489 .013 .019 -.024 .049 risk_accep Equal variances assumed 3.228 .072 -.866 32236 .386 -.058 .067 -.189 .073 Equal variances not assumed -.874 7040.476 .382 -.058 .066 -.188 .072

From the above output, we see that

• There is no significant difference in scoring the driver aggression between metro and non-metro residents (p - value = 0.475> 0.05)
• There is no significant difference in scoring the thrill seeking behaviour between metro and non-metro residents (p - value = 0.493> 0.05)
• There is no significant difference in scoring the risk acceptance between metro and non-metro residents (p - value = 0.386> 0.05)

Test Used: Independent Sample t test

Independent Variable: Study Mode

Dependent Variables: Driver Aggression Score, Thrill Score and Risk Acceptance Score

 Group Statistics STUDY_MODE N Mean Std. Deviation Std. Error Mean driver_agg FT 34770 7.51 4.344 .023 PT 3911 7.54 4.339 .069 thrill FT 34770 5.00 1.224 .007 PT 3911 5.00 1.225 .020 risk_accep FT 34770 8.51 4.355 .023 PT 3911 8.68 4.374 .070

 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 driver_agg Equal variances assumed .323 .570 -.309 38679 .757 -.023 .073 -.166 .121 Equal variances not assumed -.310 4834.453 .757 -.023 .073 -.166 .121 thrill Equal variances assumed .222 .637 .132 38679 .895 .003 .021 -.038 .043 Equal variances not assumed .132 4829.635 .895 .003 .021 -.038 .043 risk_accep Equal variances assumed .045 .832 -2.269 38679 .023 -.167 .073 -.311 -.023 Equal variances not assumed -2.261 4823.706 .024 -.167 .074 -.311 -.022

From the above output, we have

»      The mean driver aggression scoring is not high for part time students when compared to that of full time students (p - value = 0.757 > 0.05)

»      The mean thrill seeking behaviour scoring is not high for part time students when compared to that of full time students (p - value = 0.895> 0.05)

»      The mean risk acceptance behaviour scoring is high for part time students when compared to that of full time students (p - value = 0.023< 0.05)

Test Used: Independent Sample t test

Independent Variable: RTA and one or more

Dependent Variables: Driver Aggression Score, Thrill Score and Risk Acceptance Score

 Group Statistics RTA_one_crash N Mean Std. Deviation Std. Error Mean driver_agg No RTAs 33628 6.79 4.116 .022 One RTA or more 5053 12.34 2.218 .031 thrill No RTAs 33628 4.80 1.159 .006 One RTA or more 5053 6.34 .686 .010 risk_accep No RTAs 33628 7.91 4.210 .023 One RTA or more 5053 12.68 2.748 .039

 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 driver_agg Equal variances assumed 3179.609 .000 -93.863 38679 .000 -5.552 .059 -5.668 -5.436 Equal variances not assumed -144.454 11183.466 .000 -5.552 .038 -5.627 -5.476 thrill Equal variances assumed 1715.363 .000 -92.063 38679 .000 -1.539 .017 -1.572 -1.507 Equal variances not assumed -133.493 10036.697 .000 -1.539 .012 -1.562 -1.517 risk_accep Equal variances assumed 1951.956 .000 -78.154 38679 .000 -4.775 .061 -4.895 -4.655 Equal variances not assumed -106.209 9076.181 .000 -4.775 .045 -4.863 -4.687

From the above output, we have

• The mean driver aggression scoring is high for one or more RTA when compared to that of no RTA students (p - value = 0.000 < 0.05)
• The mean thrill seeking behaviour scoring is high for one or more RTA when compared to that of no RTA students (p - value = 0.000 < 0.05)
• The mean risk acceptance behaviour scoring is high for one or more RTA when compared to that of no RTA students (p - value = 0.000 < 0.05)

DO YOU WANT TO EXCEL IN PUBH620 MJA MANUSCRIPT ASSIGNMENT? HIRE TRUSTED TUTORS FROM EXPERTSMINDS AND ACHIEVE SUCCESS!

4.

Test Used: Chi Square Test for Independence

Independent Variable: Gender

Dependent Variables: Depression Scores

 Count GENDER Total Male Female depression Not depressed 9365 25355 34720 Depressed 1084 2877 3961 Total 10449 28232 38681

 Chi-Square Tests Value df Asymptotic Significance (2-sided) Exact Sig. (2-sided) Exact Sig. (1-sided) Pearson Chi-Square .280a 1 .597 Continuity Correctionb .260 1 .610 Likelihood Ratio .279 1 .597 Fisher's Exact Test .598 .305 Linear-by-Linear Association .280 1 .597 N of Valid Cases 38681 a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 1070.00. b. Computed only for a 2x2 table

Here, we see that the value of chi square test statistic is 0.597 > 0.05, indicating that the variables Gender and Depression are independent of each other

Test Used: Chi Square Test for Independence

Independent Variable: Metro

Dependent Variables: Depression Scores

 Count METRO Total Metro Non-metro depression Not depressed 24443 4495 28938 Depressed 2780 520 3300 Total 27223 5015 32238

 Chi-Square Tests Value df Asymptotic Significance (2-sided) Exact Sig. (2-sided) Exact Sig. (1-sided) Pearson Chi-Square .114a 1 .736 Continuity Correctionb .097 1 .755 Likelihood Ratio .113 1 .737 Fisher's Exact Test .743 .378 Linear-by-Linear Association .114 1 .736 N of Valid Cases 32238 a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 513.35. b. Computed only for a 2x2 table

Here, we see that the p - value of chi square test statistic is 0.736 > 0.05, indicating that the variables metro and depression are independent of each other

Test Used: Chi Square Test for Independence

Independent Variable: Study Mode

Dependent Variables: Depression Scores

 STUDY_MODE Total FT PT depression Not depressed 31241 3479 34720 Depressed 3529 432 3961 Total 34770 3911 38681

 Chi-Square Tests Value df Asymptotic Significance (2-sided) Exact Sig. (2-sided) Exact Sig. (1-sided) Pearson Chi-Square 3.072a 1 .080 Continuity Correctionb 2.975 1 .085 Likelihood Ratio 3.011 1 .083 Fisher's Exact Test .084 .042 Linear-by-Linear Association 3.072 1 .080 N of Valid Cases 38681

Here, we see that the p - value of chi square test statistic is 0.08> 0.05, indicating that the variables study mode and depression are independent of each other

NEVER LOSE YOUR CHANCE TO EXCEL IN PUBH620 MJA MANUSCRIPT ASSIGNMENT - HIRE BEST QUALITY TUTOR FOR ASSIGNMENT HELP!

5. Binary Logistic Regression

Age

 Variables in the Equation B S.E. Wald df Sig. Exp(B) 95% C.I.for EXP(B) Lower Upper Step 1a age_category 54.778 3 .000 age_category(1) .320 .057 31.249 1 .000 1.377 1.231 1.540 age_category(2) .252 .060 17.836 1 .000 1.286 1.144 1.445 age_category(3) .046 .068 .447 1 .504 1.047 .916 1.196 Constant -2.130 .053 1617.179 1 .000 .119 a. Variable(s) entered on step 1: age_category.

The odds ratio for RTA one crash for Students aged 18 years at time of enrolment 1.377, younger aged adults are at 1.4 times higher risk of involving in one or more RTA crash (p < 0.05)

The odds ratio for RTA one crash for Students aged 19 and 21 years at time of enrolment 1.286, younger aged adults are at 1.286 times higher risk of involving in one or more RTA crash (p < 0.05)

The odds ratio for RTA one crash for Students aged 22 to 25 years is1.047, indicating that the students aged 22 - 25 years  are at 1.047 times higher risk of involving in one or more crash when compared to students aged 26 years and above and statistically insignificant (p < 0.504)

Gender

 Variables in the Equation B S.E. Wald df Sig. Exp(B) 95% C.I.for EXP(B) Lower Upper Step 1a GENDER(1) .265 .033 65.690 1 .000 1.303 1.222 1.389 Constant -1.972 .018 11774.749 1 .000 .139 a. Variable(s) entered on step 1: GENDER.

The odds ratio for RTA one crash for male Students is1.303, indicating that the male students  are at 1.303 times higher risk of involving in one or more crash when compared to female students and statistically significant (p < 0.05)

Living arrangements (enter as categorical variable)

 Variables in the Equation B S.E. Wald df Sig. Exp(B) 95% C.I.for EXP(B) Lower Upper Step 1a LIVING_ARRANGE 12.178 2 .002 LIVING_ARRANGE(1) .028 .035 .605 1 .437 1.028 .959 1.102 LIVING_ARRANGE(2) .149 .045 10.958 1 .001 1.160 1.063 1.267 Constant -1.938 .029 4541.261 1 .000 .144 a. Variable(s) entered on step 1: LIVING_ARRANGE.

The odds ratio for RTA one crash for Students living in college accommodation is1.028, indicating that students who are not with their parents are at slightly higher risk in involving in RTA one or more crash, but statistically insignificant (p = 0.437> 0.05)

The odds ratio for RTA one crash for Students living independently is1.16, indicating that students who are not with their parents and living independently are at slightly higher risk in involving in RTA one or more crash, but statistically significant (p = 0.001 < 0.05)

Domestic/international status

 Variables in the Equation B S.E. Wald df Sig. Exp(B) 95% C.I.for EXP(B) Lower Upper Step 1a FEE_STATUS(1) .217 .039 31.736 1 .000 1.242 1.152 1.340 Constant -1.934 .017 13306.670 1 .000 .145 a. Variable(s) entered on step 1: FEE_STATUS.

Odds Ratio: 1.242

P - Value: 0.000

Therefore, the risk of RTA one or more crash is high for students with international status and statistically significant

Driving distance

 Variables in the Equation B S.E. Wald df Sig. Exp(B) 95% C.I.for EXP(B) Lower Upper Step 1a dist_driving -.016 .031 .268 1 .605 .984 .926 1.046 Constant -1.885 .024 5937.971 1 .000 .152 a. Variable(s) entered on step 1: dist_driving.

Odds Ratio: 1.242

P - Value: 0.000

Therefore, the variable driving distance is not significant predictor of RTA one or more crash

Aggression

 Variables in the Equation B S.E. Wald df Sig. Exp(B) 95% C.I.for EXP(B) Lower Upper Step 1a driver_agg .457 .007 4638.311 1 .000 1.580 1.559 1.601 Constant -6.495 .081 6474.348 1 .000 .002 a. Variable(s) entered on step 1: driver_agg.

Odds Ratio: 1.58

P - Value: 0.000

Therefore, the risk of RTA one or more crash is 1.58 high for students whose driving aggression score increases by one unit and statistically significant

Thrill-seeking

 Variables in the Equation B S.E. Wald df Sig. Exp(B) 95% C.I.for EXP(B) Lower Upper Step 1a thrill 1.487 .021 4901.218 1 .000 4.425 4.245 4.613 Constant -10.332 .131 6179.082 1 .000 .000 a. Variable(s) entered on step 1: thrill.

Odds Ratio: 4.425

P - Value: 0.000

Therefore, the risk of RTA one or more crash is 4.425 high for students whose thrill seeking score increases by one unit and statistically significant

Risk acceptance

 Variables in the Equation B S.E. Wald df Sig. Exp(B) 95% C.I.for EXP(B) Lower Upper Step 1a risk_accep .335 .005 3959.400 1 .000 1.397 1.383 1.412 Constant -5.433 .067 6641.557 1 .000 .004 a. Variable(s) entered on step 1: risk_accep.

Odds Ratio: 1.397

P - Value: 0.000

Therefore, the risk of RTA one or more crash is 1.397 high for students whose risk acceptance score increases by one unit and statistically significant

ORDER NEW PUBH620 MJA MANUSCRIPT ASSIGNMENT & GET 100% ORIGINAL SOLUTION AND QUALITY WRITTEN CONTENTS IN WELL FORMATS AND PROPER REFERENCING.

6.

Age

 Variables in the Equation B S.E. Wald df Sig. Exp(B) 95% C.I.for EXP(B) Lower Upper Step 1a age_category 54.778 3 .000 age_category(1) .320 .057 31.249 1 .000 1.377 1.231 1.540 age_category(2) .252 .060 17.836 1 .000 1.286 1.144 1.445 age_category(3) .046 .068 .447 1 .504 1.047 .916 1.196 Constant -2.130 .053 1617.179 1 .000 .119 a. Variable(s) entered on step 1: age_category.

Odds Ratio: 1.377

P - Value: 0.000

Therefore, the risk of obese is 1.377 high for students whose age at the time of enrolment is 18 years and statistically significant

Odds Ratio: 1.286

P - Value: 0.000

Therefore, the risk of obese is 1.286 high for students whose age at the time of enrolment is 19 and 21 years and statistically significant

Odds Ratio: 1.047

P - Value: 0.504

Therefore, the risk of obese is 1.286 high for students whose age at the time of enrolment is 22 and 25 years and statistically significant

Gender

 Variables in the Equation B S.E. Wald df Sig. Exp(B) 95% C.I.for EXP(B) Lower Upper Step 1a GENDER(1) .265 .033 65.690 1 .000 1.303 1.222 1.389 Constant -1.972 .018 11774.749 1 .000 .139 a. Variable(s) entered on step 1: GENDER.

Odds Ratio: 1.303

P - Value: 0.000

Therefore, the risk of obese is 1.303 high for male students when compared to that of female counterparts and statistically significant

Living Arrangements

 Variables in the Equation B S.E. Wald df Sig. Exp(B) 95% C.I.for EXP(B) Lower Upper Step 1a LIVING_ARRANGE 12.178 2 .002 LIVING_ARRANGE(1) .121 .040 9.073 1 .003 1.129 1.043 1.221 LIVING_ARRANGE(2) -.028 .035 .605 1 .437 .973 .908 1.043 Constant -1.910 .021 8541.127 1 .000 .148 a. Variable(s) entered on step 1: LIVING_ARRANGE.

Odds Ratio: 1.028

P - Value: 0.437

Therefore, the risk of obese is 1.028 high for students who use college accommodation and statistically insignificant

Odds Ratio: 0.973

P - Value: 0.001

Therefore, the risk of obese is 0.973lessrisk for students are living independently and statistically significant

Overweight or obese at baseline

 Variables in the Equation B S.E. Wald df Sig. Exp(B) 95% C.I.for EXP(B) Lower Upper Step 1a BL_owob(1) -.016 .031 .268 1 .605 .984 .926 1.046 Constant -1.885 .024 5937.971 1 .000 .152 a. Variable(s) entered on step 1: BL_owob.

The variable overweight or obese at baseline act as a protective factor for obese and statistically insignificant I(p > 0.05)

Depression at baseline

 Variables in the Equation B S.E. Wald df Sig. Exp(B) 95% C.I.for EXP(B) Lower Upper Step 1a depression(1) 1.787 .037 2325.604 1 .000 5.970 5.552 6.420 Constant -2.197 .018 15085.364 1 .000 .111 a. Variable(s) entered on step 1: depression.

Odds Ratio: 5.97

P - Value: 0.000

Therefore, the risk of obese is 5.97 high for Students who are depressed at baseline and statistically significant

Parental factors

 Variables in the Equation B S.E. Wald df Sig. Exp(B) 95% C.I.for EXP(B) Lower Upper Step 1a edu_par -2.726 .054 2535.296 1 .000 .065 .059 .073 Constant -.943 .017 3028.510 1 .000 .390 a. Variable(s) entered on step 1: edu_par.

Odds Ratio: 5.97

P - Value: 0.000

Therefore, the risk of obese is 0.065 times less risk for Students whose parents education increases by one year and statistically significant.

GETTING STUCK WITH SIMILAR PUBH620 MJA MANUSCRIPT ASSIGNMENT? ENROL WITH EXPERTSMINDS'S PUBH620 MJA MANUSCRIPT ASSIGNMENT HELP SERVICES AND GET DISTRESSED WITH YOUR ASSIGNMENT WORRIES!

Access the major courses cover under our Australian Catholic University Assignment Help Service:-

• PUBH200 Globalisation, environment and health Assignment Help
• PUBH306 Public Health Policy and Law Assignment Help
• UNCC300 Justice and change in a global world Assignment Help
• PUBH305 Applied public health Assignment Help
• PUBH205 Public health emergency response Assignment Help
• PUBH303 Applied Public Health Communication Assignment Help
• PUBH311 Contemporary Issues in Public Health Assignment Help
• PUBH100 Foundations in Public Health Assignment Help
• PUBH312 Applied Health Promotion Assignment Help

Tag This :- WPS9020052305BSTAT, PUBH620 MJA Manuscript Assignment Help

### Assignment Samples

 Business Research Project – Cryptocurrency Assignment Help business research project – cryptocurrency assignment help - combine many facets of your acquired MBA skills into production of a high-quality research project Sustainable Development Assignment Help sustainable development assignment help - What factors have gone into making this team either a success or dysfunctional? How could the team be improved? Change Things - Data Analytics Assignment Help change things - data analytics assignment help - Write an Annotated Bibliography for your Capstone Topic with a collection of 12 articles Motivation Assignment Help motivation assignment help - This paper highlights the requirement of the new aims to match with the desired understanding of traits. Linear Scheduling Model Assignment Help linear scheduling model assignment help - Research of Linear Scheduling Model with Varying Production Rates. Web Design Pitch and Proposal Assignment Help web design pitch and proposal assignment help - Prepare a professional web design and development proposal in the form of a PowerPoint presentation HMGT 372 Healthcare Environment Assignment Help hmgt 372 healthcare environment assignment help- ACHE is a professional body that is working on improving the health of the patients and communities. They are w

Get Academic Excellence with Best Skilled Tutor! Order Assignment Now!