Jamovi PART 1 PDF

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Psychology Research Methods (HPS201/HPS771) Assignment Kabison Kamalamohan 216143282

Task 1: Chi-square Analysis

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Experiment 1 According to recent media, postgraduate students prefer online learning to face-to-face learning (AFR, 12 October 2020). However, while this view may apply to postgraduate students, it is not known whether undergraduate students hold the same view as postgraduate students. To investigate this question, you recruit a sample of 80 students. You then classify each student as either an undergraduate student or postgraduate student. For each student, you also record whether they prefer face-to-face learning or online learning. The data from this study can be found in the file digital_learning.omv. The variable StudentType indicates whether a student is an undergraduate or a postgraduate student. The variable StudyPref gives an indication of a student’s preferred study mode. Experiment 1 - Questions 1. Conduct the appropriate Chi-square test examining the association between student type (undergraduate or postgraduate) and preferred study mode (face-to-face or digital). Attach the relevant jamovi output to your submission. (3 Marks) 𝐻0 : There is no association between student type and study preference. 𝐻1 : Study preference is dependent on student type

2. With help from the unit materials, report the results of the analysis in APA format including all relevant information. (3 Marks)

A Chi-square Test of Independence was conducted to test if study preference is associated with student type. The results of the analysis suggested that there is no association between student type and study preference, χ2 (df = 1, N = 80) = 3.20, p = .074, ϕ = .20.

Experiment 2 Dr Bean claims that students who drink coffee are more likely to score a High Distinction (HD) on their Research Methods exam than students who don’t drink coffee. To evaluate this claim, Dr Bean recruits a sample of university students and classifies each student according to their coffee drinking behaviour (whether they drink coffee or not). For each student, Dr Bean also records their exam performance (whether they scored an HD or not). Dr Bean then runs a Chisquare analysis to test for an association between exam performance and coffee drinking behaviour. Statistical Output

Based on the jamovi output and the background information provided, Dr Bean reports the results of the analysis as follows: A Chi-square Goodness of Fit Test was conducted to test if exam performance was associated with coffee drinking behaviour. The analysis suggested that students who drink coffee are significantly more likely to score a HD on their exam than students who do not drink coffee, 2(df = 1, N = 60) = 5.18, p = .023,  = .92. Experiment 2 - Questions 1. List any factual mistakes made by Dr Bean in the above statement. For each mistake, note why Dr Bean is incorrect. (2 Marks) The first factual mistake is the type of test used. The test is supposed to be a Chisquare test for association or independence, not a Chi-square Goodness of Fit Test. A Goodness of Fit test is used when comparing a sample data against a population distribution and whether the sample fits with the distribution. However, this test only checks whether there is an association between coffee and a high distinction score.

Another factual mistake is that the value of ϕ. The reported result lists its value as .92, when the output table lists it at .29.

2. Re-write Dr Bean’s statement after correcting any mistakes made. (2 Marks) A Chi-square Test of Independence was conducted to test if exam performance was associated with coffee drinking behaviour. The analysis suggested that students who drink coffee are significantly more likely to score a HD on their exam than students who do not drink coffee, χ2 (df = 1, N = 60) = 5.18, p = .023, ϕ = .29. Psychology Research Methods Introductory (HPS201/HPS771) Assignment Task 2: t-tests ______________________________________________________________

Experiment 1 Research suggests that Attention Deficit Hyperactivity Disorder (ADHD) is frequently accompanied by motor coordination problems (Kaiser et al., 2015). To investiage this empirically, you take a sample of 80 children who have been diagnosed with ADHD and a second sample of 80 children without ADHD of the same age. You then assess each child’s motor coordination using the Developmental Coordination Disorder Questionnaire (DCD-Q), a parent report measure developed to assist in the identification of motor difficulties. Higher scores on the DCD-Q indicate higher levels of motor coordination. The data from this study can be found in the file DCDQ.omv. The variable Group indicates whether a participant was assigned to the ADHD group or the non-ADHD group. The variable DCDQ indicates the obtained DCD-Q score for each participant. Experiment 1 - Questions 1. Conduct the appropriate t-test to test whether the mean DCD-Q score of the ADHD group is different from the mean DCD-Q score of the non-ADHD group. Attach the relevant jamovi output to your submission. (2 Marks)

2. With help from the unit materials, report the results of the analysis in APA format including all relevant information. (3 Marks) The mean DCD-Q score of ADHD was observed to be different from mean DCD-Q score of the non-ADHD group, t(158) = 2.72, p = .007. Difference in scores had a moderate effect size, Cohen’s d = 0.43, 95% CI [1.54, 9.69].

3. Assume you are a clinical psychologist. On the basis of the results of the study, what would be your recommendation for the assessment and/or treatment of children with ADHD? Justify your answer by discussing the observed difference in motor coordination between children with ADHD and typically developing children. (1 Mark) From the analysis, it is evident that the motor coordination of children with ADHD is different from others. I would recommend developing special regimented programmes that put emphasis on motor skills training so that their growth curve is similar to others.

Experiment 2 Dr Zumba would like to examine the effectiveness of a motor training program in improving motor skills in a group of children with ADHD. In the study, a group of children with ADHD complete tasks assessing their balance and strength before (PreStrength / PreBalance) and after (PostStrength / PostBalance) undertaking the motor training program. Higher scores on the strength and balance tasks indicate better performance. Dr Zumba then conducts the following statistical analyses: Statistical Output

Experiment 2 – Questions Answer the following questions with reference to the appropriate statistical output. You are not required to respond in APA format. 1. Dr Zumba concludes that the training program is effective in improving both balance and strength in children with ADHD. Is Dr Zumba correct? Justify your response. (2 Marks) Dr Zumba is correct. This is because p-value for both hypothesis tests was less than 0.01 resulting in rejection of null hypothesis which assumed that there is no difference between the strength and balance before and after the training.

2. What would you consider to be the most appropriate interpretation of the analyses conducted (select one of the below response options)? Justify your response. (2 Marks) A) Children with ADHD would be expected to show greater change in balance than in strength following the training program. B) Children with ADHD would not be expected to show change in either strength or balance following the training program. C) Children with ADHD would be expected to show greater change in strength than in balance following the training program. D) Children with ADHD would be expected to show equal change in both strength and balance following the training program. Option C is correct. This is because although both claims were accepted, the test statistic for paired t-test of pre and post strength (t = 12.51) was significantly higher than that of pre and post balance (5.20) showcasing that the strength gain was more than the change in balance.

Psychology Research Methods Introductory (HPS201/HPS771) Assignment Task 3: Correlation ______________________________________________________________

Experiment 1 Mindfulness programs have become increasingly popular in the workplace and are now commonly adopted by blue chip business es such as Google (Financial Times, 2015). Specifically, recent evidence suggests that regular mindfulness practice may be associated with employee well-being. To test this, you take a sample of 80 Google employees and ask them how many mindfulness sessions they attended in the past year. You also ask them how many sick days they took. The data from this study can be found in the file Mindfulness.omv. The variable Mindfulness indicates the number of mindfulness sessions each participant attended in the past year. The variable SickDays indicates the number of sick days each participant took. Experiment 1 - Questions 1. Plot the data in jamovi using a scatterplot. Based on the scatterplot alone, describe thetype, direction and strength of the observed association. Justify your response. (3 Marks)

The scatter plot indicates that there is a negative correlation between sick days taken and number of mindfulness sessions. The strength of the plot is moderate.

2. Conduct a correlation analysis to investigate the association between the number of mindfulness sessions attended and the number of sick days taken (attach the relevant jamovi output to your submission). Report the results of the analysis in APA format including all relevant information. (3 Marks)

The variables sick days and mindfulness sessions were found out to be negatively correlated, r(78) = -.71, p-value < .001.

3. Assume you are an Organizational Psychologist. What would be your recommendation to Google based on the results of this study? Justify your response. (1 Mark) As an organizational psychologist, I would suggest Google to conduct more number mindful sessions. Since there is evidence of negative correlation from the correlation analysis between number of sick days taken and the number of mindful sessions, increasing number mindful sessions would decrease the number of sick leaves taken by the employees.

Experiment 2 Dr Insomnia is interested in factors that influence attention span. She asks a sample of 40 individuals to complete an attention span task that measures maximum attention span in seconds (higher scores indicate greater attention span). For each participant, Dr Insomnia also records their age and the average number of hours slept in the previous week. Finally, Dr Insomnia obtains a measure of intelligence for each participant (higher scores indicate higher levels of intelligence). The data from this study can be found in the file Insomnia. The variable AttentionSpan indicates performance on the attention span task. The variables Age and HoursSlept indicate the age of the participant and the number of hours slept in the past week respectively. The variable Intelligence indicates each participant’s intelligence score.

Experiment 2 – Questions Use jamovi to assist you in answering the following question. You are not required to attach the jamovi output for this analysis to your submission. 1. Of the variables measured, Dr Insomnia concludes that age is the most relevant factor for explaining individual differences in attention span. Based on the data collected, is Dr Insomnia correct? Justify your response by ranking the factors associated with attention span from most relevant to least relevant. (3 Marks). Based on the data collected, Dr Insomnia is not correct. The most relevant factor for explaining individual differences in attention span is hours of sleep as the correlation between attention span and age is 0.507 while the correlation between hours of sleep and attention span is -0.619. The factors that affect the attention span ranking from most to least relevant are hours of sleep, age and intelligence....