Explain how the conditions differ on GPA, distraction, and number of texts received.

Words: 365
Pages: 2
Subject: Do My assignment

First, a researcher has randomized students into one of two conditions- restricted phone use (High Restriction) and no restriction (Low Restriction). Our researchers would like to know the following: How the conditions differ on GPA, distraction, and number of texts received. Next, our researchers are trying to see if watching reality tv impacts self esteem. Use the pairedttest data set to run a paired samples t-test using the pre and post test scores. For each test (4) please write the results in APA format using the format below as an example (please be sure to change information to match your results and the study concept). Submit the SPSS output (exported as a pdf preferred) and the results write up. Reminder: You will have four write-ups! How to write t-test results in APA: Independent T-Test Significant p-value: The [n] participants [grouping variable] (M = [mean], SD = [standard dev]) compared to the [n] participants in the [grouping variable] (M = [mean], SD = [standard dev]) demonstrated significantly [dependent variable], t(df) = [t-statistic], p [=/< p-value]. Non-significant p-value: There was no significant effect for [grouping variable], t(df) = [t-statistic], p [=/< p-value], despite [group] (M = [mean], SD = [standard dev]) [description of scores- higher lower variable scores] than [group] (M = [mean], SD = [standard dev]). Dependent/Paired Samples T-Test Significant p-value: The results from the pre-test (M = [mean], SD = [standard dev]) and post-test ((M = [mean], SD = [standard dev]) [paired variable] indicate that the [independent variable] in resulted in [increase/decrease/improvement/worsening/etc] in [DV], t(df) = [t-statistic], p [=/< p-value]. Non-significant p-value: There was a no significant difference in the [dependent variable] in [paired variable pretest] (M = [mean], SD = [standard dev]) compared to [paired variable posttest] (M = [mean], SD = [standard dev]), t(df) = [t-statistic], p [=/< p-value].

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