STA20006 Analysis of Variance and RegressionThis assignment relates to the SPSSAssignment 1 data...

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STA20006 Analysis of Variance and RegressionThis assignment relates to the SPSSAssignment 1 data file (SAV 9 KB)			download. The objective of this assignment is for you to understand research scenarios that concern correlation and regression. In particular, it is important that you master the components of multiple regression, such as moderation and mediation, as these techniques are regularly used within the Health Sciences.Please note that all relevant statistical SPSS output should be placed in an appendix at the end of your document.This assignment supportsunit learning outcomes 1, 2, 3, 4, 5, 6 and 7.10/08/2021 Assignment 2: Workbook assignment part 1 tasks: Analysis of Variance and Regression https://swinburneonline.instructure.com/courses/3012/pages/assignment-2-workbook-assignment-part-1-tasks 1/6 Assignment 2: Workbook assignment part 1 tasks It is recommended that you use the STA20006 Answer template assignment 2 (DOCX 30 KB) (https://swinburneonline.instructure.com/courses/3012/files/2061221/download?wrap=1)  (https://swinburneonline.instructure.com/courses/3012/files/2061221/download? download_frd=1) to help you format the answers to each of the following tasks. You can additionally add your SPSS outputs in this template. Information on the data collected Data for Assignment 2: Workbook assignment part 1 tasks Variable Variable coding Variable description ID N/A The identification number allocated to each participant. Sex 0: Male 1: Female The sex of the participant. Age N/A The age of the participant. Load 0: Full-time 1: Part-time The workload of the participant. Residency 0: Citizen/permanent resident 1: International The participant's residency status. Satisf N/A A measure of the participant’s satisfaction with their current work.  Work satisfaction scores range from 0 to 80, with a https://swinburneonline.instructure.com/courses/3012/files/2061221/download?wrap=1 https://swinburneonline.instructure.com/courses/3012/files/2061221/download?download_frd=1 10/08/2021 Assignment 2: Workbook assignment part 1 tasks: Analysis of Variance and Regression https://swinburneonline.instructure.com/courses/3012/pages/assignment-2-workbook-assignment-part-1-tasks 2/6 higher score indicating higher levels of work satisfaction. Income N/A The participant's annual income. Partinc N/A The participant's partner/spouse's annual income. YearsComp N/A The number of years the participant has been employed at the current company. TravelTime N/A The time taken (in minutes) for the participant to travel to work each day. YearsEdu N/A The number of years of tertiary education the participant received. IQscore N/A A measure of the participant’s intelligence quotient. Task A: Report (18%) The research team at a large Melbourne based company has hypothesised that workers who take less time to travel to work each day will generally be more satisfied with their work life. Use the data from the Assignment 1 data file (SAV 9 KB) (https://swinburneonline.instructure.com/courses/3012/files/2251844/download?wrap=1)   (https://swinburneonline.instructure.com/courses/3012/files/2251844/download? download_frd=1) file to investigate this hypothesis. Write a brief report on your results, including an appropriate hypothesis test. Quote all relevant statistics and appendix relevant output. In addition, refer to the following notes:  Note 1: Assume all assumptions have been met. Note 2: Check the marking rubric to see how this question is graded. Note 3: The report should be written in APA format. Task B: Multiple regression (18%) In a follow-up study, the researchers decided to investigate the factors that affect the number of years participants in their sample of Australian adults are employed at a company. The researchers included the following predictors in their model: work satisfaction, years of tertiary education and sex. Using the Assignment 1 data file (SAV 9 KB) (https://swinburneonline.instructure.com/courses/3012/files/2251844/download?wrap=1)   (https://swinburneonline.instructure.com/courses/3012/files/2251844/download? https://swinburneonline.instructure.com/courses/3012/files/2251844/download?wrap=1 https://swinburneonline.instructure.com/courses/3012/files/2251844/download?download_frd=1 https://swinburneonline.instructure.com/courses/3012/files/2251844/download?wrap=1 https://swinburneonline.instructure.com/courses/3012/files/2251844/download?download_frd=1 10/08/2021 Assignment 2: Workbook assignment part 1 tasks: Analysis of Variance and Regression https://swinburneonline.instructure.com/courses/3012/pages/assignment-2-workbook-assignment-part-1-tasks 3/6 download_frd=1) , run a multiple regression to address this scenario and answer the following questions: From the raw correlations table, which of the predictors were significantly related to the dependent variable? Quote relevant statistics. Give the regression equation for the number of years spent working for a company (to two decimal places). Use the regression equation to predict the number of years spent working for a company for a male who has a work satisfaction score of 40 and 4 years of tertiary education. Interpret the partial regression coefficient for work satisfaction. What was the most important predictor in this regression? Quote relevant statistics. When all of the predictors are taken into account, what predictors contributed significantly to the multiple regression? Quote relevant statistics. Is the value of Multiple R significant? What does this tell us? Quote relevant statistics. How much of the variation in the number of years spent working for a company can be explained by this linear model? In addition, consider the following notes: Note 1: Assume all assumptions have been met. Note 2: When quoting relevant statistics, use APA format. Note 3: Check the marking rubric to see how this question is graded. Task C: Error identification (18%) In a follow-up study, the researchers decided to investigate the factors that affect annual income for their sample of office workers. The researchers included the following predictors into their model: age, years of tertiary education and sex. The researchers hypothesised that: People with more years of tertiary education will have higher annual incomes. Older people will have higher annual incomes. Males will have higher annual incomes than females. Using the data from the Assignment 1 data file (SAV 9 KB) (https://swinburneonline.instructure.com/courses/3012/files/2251844/download?wrap=1)   (https://swinburneonline.instructure.com/courses/3012/files/2251844/download? download_frd=1) , the researchers have provided a report to address these research hypotheses. Section 1 https://swinburneonline.instructure.com/courses/3012/files/2251844/download?download_frd=1 https://swinburneonline.instructure.com/courses/3012/files/2251844/download?wrap=1 https://swinburneonline.instructure.com/courses/3012/files/2251844/download?download_frd=1 10/08/2021 Assignment 2: Workbook assignment part 1 tasks: Analysis of Variance and Regression https://swinburneonline.instructure.com/courses/3012/pages/assignment-2-workbook-assignment-part-1-tasks 4/6 A study was conducted to explore factors affecting the annual income of workers from a Melbourne-based company. The researchers proposed that people with more years of tertiary education would have higher annual incomes. They also suggested that older people would have higher annual incomes. Finally, they suggested that males would have higher annual incomes than females. A multiple regression was performed on this data with income as the dependent variable. Three predictors were included in the model: age, years of tertiary education and sex (male/female).  The intercorrelations between the variables are given in Table 1, and the regression statistics are given in Table 2. Table 1: Intercorrelations among the variables  Income Age Year T.Edu Age .43*** Years T.Edu .77*** .44*** Sex -.06 -.04 -.02 Note: *p

Suraj · Accepted Answer

ANALYSIS OF VARIANCE AND REGRESSION 
Name: [Your Name]
Student ID: [Your ID number]
TASK A
Introduction: We are given the data set of the employees. There are many variables in the data set. The research team at a large Melbourne based company has hypothesised that workers
who take less time to travel to work each day will generally be more satisfied with their work life.
Here, we are interested only on two variables. Those two variables are the Travel time and Satisf.
The level of measurement of the two variables are Interval scale for Satisf variable because the data is taken on a particular interval between 0 to 80 and the Travel time is measured on Ratio scale.
Question of interest: Here, the research team at a large Melbourne based company has hypothesised that workers who take less time to travel to work each day will generally be more satisfied with their work life. Thus, this question is based on the correlation analysis. That we need to check that both the variables are negatively correlated to each other.
It is mentioned that the assumptions are satisfied but we will cross check the most important assumption of correlation analysis i.e., the linear relationship. For this we will use the scatter plot and plot the values on it.  We will assume Travel time as our explanatory variable and Satisfaction score as the response variable.
Let  be the population correlation coefficient. The hypotheses are given as follows:
There is no correlation between travel time and satisfaction score i.e., .
There is a significant negative correlation between travel time and satisfaction score i.e., .
The correlation analysis is conducted using the SPSS and the correlation coefficient calculated between two variables is -0.488 and the corresponding p-value is 0. Thus, the p-value is less than the level of significance 0.05. hence, the null hypothesis is rejected and we concluded that there is a significant negative correlation between these two variables. Hence, we support the claim of the researcher that the workers who take less time to travel to work each day will generally be more satisfied with their work life.
APPENDIX A
Any output you produced for Task A
Scatter Plot for linear relationship
Pearson Correlation Analysis Table
TASK B
Research Question: The researchers decided to investigate the factors that affect the number of years participants in their sample of Australian adults are employed at a company. The researchers included the predictors in their model given as follows: work satisfaction, years of tertiary education and sex and the dependent variable is the Years Comp.

STA20006 Analysis of Variance and Regression This assignment relates to the SPSSAssignment 1 data file (SAV 9 KB) download. The objective of this assignment is for you to understand research scenarios...

STA20006 Analysis of Variance and Regression

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