University : CQUniveristy UniLearnO is not sponsored or endorsed by this college or university.
Subject Code : PSYC11012
Country : Australia
Assignment Task

 

OVERVIEW

Your research report will explore the relationship between social media use (SMU) and procrastination. This document contains the data you need to write the Method and Results sections of your report. This document is divided into three sections:

  • Descriptive Statistics
  • Inferential Statistics
  • What does it all mean?

 

The data contained within the Descriptive Statistics and Inferential Statistics sections MUST be included in your report and formatted according to American Psychological Association (APA) standards, 7th edition. Please also refer to the additional information provided in the lectures, on the Moodle site (including the original Research Report Handout and instructional video), and in the recommended texts for this Unit, for further guidance on what to include in your report.

The analyses outlined below were calculated using an industry-standard analysis program, called IBM SPSS, version 25. You will learn more about this program as you progress through your psychology degree. The raw Excel data file for this study has also been made available on Moodle; you may consult this, if you would like to see what the unprocessed data looks like. 

 

Descriptive Statistics 

The information in the box below MUST be reported in the Method section of your report, under the Participants sub-heading. The descriptive demographic data given here needs to be reported in written form (i.e., the important information needs to be taken out of the tables below and written in the text of the report). Do not present it in bullet-point or raw-table form like we have here; of course, the content, therein, can be presented in an APA-formatted table if you prefer, but if you do this, remember to also refer to the table in the text of your report (e.g., ‘See Table 1’).

 

Summary -

79 students from CQUniversity, Australia participated in the survey.

12 participants were excluded from statistical analysis, due to incomplete datasets or non-typical use on all three reporting days.

One of the remaining 67 participants, reported not using social media at all during the three-day recording period.

 

Question: What is your age in years?

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 Question: What is your sex?

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Inferential Statistics 

This section of the handout contains output taken directly from the above-mentioned SPSS statistical analysis program. The information in this section should be reported in the Results section of your report. It includes: 

 

Results from a Correlation Analysis 

  • A Pearson correlation analysis was conducted on the data.
  • The analysis compared social media use (operationalised as the average number of minutes spent using all social media accounts over the three days) and procrastination.

 

A Visual Representation of the Data

In order to visually represent the relationship between the two variables, we have used a scatterplot.

Figure 1 shows the relationship between students’ average daily social media use (SMU; on the x-axis) and their procrastination score (on the y-axis). 

Higher social media use (x-axis) indicates a greater tendency to procrastinate (y-axis).

A line that best fits the data that we collected, statistically speaking, has also been inserted. This line helps determine if the relationship is positive, negative, or neutral

 

An example write-up. The SPSS output is given, colour-coded, and linked to information on what it means, as well as an example of how to include this information in the Results section of your report.

SMU and Procrastination - 

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Scatterplot and line of best fit depicting participants’ average daily time for social media use (SMU; x-axis) in minutes, by their score on the general procrastination scale (Sirois et al., 2019; y-axis).

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What does it all mean?

Correlation analyses provide three useful pieces of information: 

  • If there is a statistically significant linear trend in the data (indicated by a p-value of less than .05. A p-value of between .05 and .10 indicates that there is a trend for the variables to relate to one another in a linear fashion, but there is still too much noise in the data to be sure of any effects (in this case, caused by a low sample size/not enough statistical power)
  • The nature of the relationship. A positive relationship is one where, as scores on one variable increase, scores on the other also increase. A negative relationship is on where, as scores on one variable increase, scores on the other decrease. This is indicated by whether the Pearson Correlation coefficient is positive or negative, respectively 
  • The size of the relationship. This is also indicated by the Pearson Correlation coefficient (a value between -.30 and .30 indicates a weak relationship). Please also see the information table, taken from Cohen (1992), below:

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You will be required to write up these results in your research report, according to APA format.

 

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