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Respond to paper below by answering question following:

1. Do you think the variables are appropriately used? Why or why not?

2. Does the addition of the control variables make sense to you? Why or why not?

3. Does the analysis answer the research question? Be sure and provide

constructive and helpful comments for possible improvement.

4. If there was a significant effect, comments on the strength and its

meaningfulness.

5. As a lay reader, were you able to understand the results and their implications?

Why or why not?

6. You need to provide at least 3 resources citing in APA style and from past 5 years

PAPER to ANALYZE:

Analyzing the High School Longitudinal Survey Dataset with the participant’s sex, hours spent

playing video games on a typical school day and the hours spent watching television on a typical

school day.

Research Question

Does the student’s sex (X1SEX) impact the hours spent playing video games on a typical school

day (S1HRTV) and the hours spent watching television or movies on a typical school day

(S1HRVIDEO)?

Null Hypothesis

H1: Do relationships exist between the participants sex and the hours per day playing video

games on a typical school day?

Ho: Do relationships exist between the participant’s sex and the hours per day spent watching

television or movies on a typical school day?

Research Design, Dependent Variable, and Independent Variable

The multiple regression model investigates the impact of several independent variables on a

single dependent variable being an appropriate instrument to answer the research question

(Frankfort-Nachmias & Leon-Guerrero, 2020). The dependent variable is the students’ sex. The

dependent variable could be collected in a database, like the SPSS statistical analysis program.

The independent variables could be collected in a survey or database reporting the number of

hours spent daily playing on a typical school day and the number of hours spent watching

television or watching movies on a typical school day.

Justification for Adding the Variables

When adding variables there is a need to control the effects of the independent variables. The

charts below indicate the number of hours playing video games per school day and the number of

hours watching television/movies on a typical school day. The Coefficient chart, Table 4, shows

that the constant is the unstandardized coefficient is 1.634. The 1.634 is where the regression

line crosses the y-axis. Therefore, for every unit increase in the hours of playing video games on

a typical school day will change at a rate of .052 units. The change of -.153 units of watching

television on a typical school day.

Significance, Strength of the Effect

According to Table 2, Model Summary, the r square is .151 and the adjusted r square is .150.

Table 2, the ANOVA, shows that the statistical significance is .000. Therefore, that .000 is less

than the .05 that is typical (Frankfort-Nachmias & Leon-Guerrero, 2020). According to Table 4,

Coefficients, .052 for the number of hours students play video games on a typical school day and

-.153 for the number of hours students watch television or movies on a typical school day. The

null hypothesis would be rejected for this data.

Explanation of Research Question

The significant level of .000 shows that the data is significant. Therefore, there is a link between

sex and the hours a student plays video games and watches television or movies on a typical

school day. The null hypothesis would be rejected based on the data.

References

Frankfort-Nachmias, C., & Leon-Guerrero, A. (2020). Social statistics for a diverse

society (8th ed.). Thousand Oaks, CA: Sage Publications.

Laureate Education (Producer). (2016g). Multiple regression [Video file]. Baltimore, MD:

Author.

Wagner, W. E. (2020). Using IBM® SPSS® statistics for research methods and

social science statistics (7th ed.). Thousand Oaks, CA: Sage Publications.

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