100013: Experimental Design And Analysis - Statistics Assessment Answer

Subject Code: 100013

Statistics Assessment Answer

Assignment Task: 100013 Assessment 1 (Autumn Semester 2019) Assessment 1 contains six research scenarios.  For each scenario, you are assuming the role of a researcher employed by different organisations for the purpose of helping them find solutions to questions they have about their business practice. Each scenario is worth 15 marks (meaning the overall assessment is out of 90, which is then divided by 3 to total 30% of the unit’s mark). Each scenario consists of the following tasks; TASK 1 For Task 1, analyse the data provided in each scenario using the relevant statistical technique (using SPSS, or perhaps even “by hand” if a z-test is appropriate). Read the scenario carefully – the analysis required will be either a one-sample z-test, a one sample t-test, a dependent samples t-test or an independent samples t-test (and because there are six scenarios, the same type of analysis might be applicable to more than one scenario). As a first step, use the tutorials, e-topics, and the foolproof guide to help you write a draft results section incorporating your statistical findings.  These results will contain the necessary statistical values required to answer a list of subsequent questions. Specifically, in the draft results you should include; (a) The Hypothesis. (b) The overall number of participants, and the means and standard deviations of the AGE of these participants, grouped by sex (Hint: if you find participants with missing data, remove them completely from the data before you perform any further analysis, including age and frequency). (c) Tests of parametric assumptions (outliers and normality) OUTLIERS HINT if you test for outliers, for the sake of simplicity perform the z-score calculations on the data as a single group of scores; in other words, don’t “split file” by Sex, Group or any other variable. However, should the scenario involve participants who each provide more than one number as their personal data – meaning a repeated measures design with multiple columns - then test each column of data separately for the presence of outliers.  If you find any outliers, modify them immediately according to the technique we learned about in class (the “plus one” or “minus one” method).  If you do discover (and then change) an outlier, you do not have to re-run the outlier analysis again. NORMALITY HINT Regarding normality, test this assumption separately for the two groups if the scenario is asking for an independent samples t-test (add “group” to the Factor list in “Explore”). For a dependent samples t-test, examine normality for each column separately – there’ll be two columns of data associated with each participant.  That means adding two columns in the Dependent list in “Explore”, and nothing in the Factor list. For one-sample z and t-tests, there’s only one column of data for a single group, so you only need to perform a single normality test. If you find any data is NOT normally distributed using a Test of Normality, you need to report this assumption violation in the draft results, simply mentioning that any statistical result “should be interpreted with caution”.  You don’t need to do anything else other than identify the potential normality violation. (d) The appropriate statistical findings (e.g., t-test results) (e) A brief interpretation of the statistical findings (f) Effect sizes and confidence intervals (only include for a scenario if appropriate). Once you have written the draft results section, you will be able to answer the questions that follow. TASK 2: Describe your research findings. For this task you will need to choose the SINGLE correct statement (from four provided) which best describes your statistical findings. TASK 3:  Identify a design flaw in the scenario. Each scenario has a major experimental design flaw, potentially affecting your statistical finding and leading to an inaccurate or invalid conclusion.  For this task, name this flaw as a single word, phrase or single sentence ONLY. Submission of Assessment 1 is through Turnitin; See vUWS and the learning Guide for further information.  The Turnitin Link will be in your Assessment Folder. TYPE YOUR ANSWERS INTO THIS WORD DOCUMENT, IN THE SPACE PROVIDED UNDER EACH TASK (The Foolproof Guide will be valuable assistance in completing each of these six tasks – however note that the results section applicable to each of the six assessment scenarios will not necessarily match “word for word” the examples shown in the Foolproof guide – for example assumptions met in the Foolproof guide example might not be met in the corresponding Assessment 1 scenario, or vice versa.  Be aware of these differences and adapted your results sections accordingly). Scenario 1 A large food manufacturing company seeks to determine the cleanliness attitudes of their 250 employees, compared to the general population.  You are tasked to compare the cleanliness attitudes of a sample of employees with the population cleanliness attitude. You measure employees’ responses using the Happiness at Work Scale, which validly measures work happiness.  This scale provides a number from 1 to 50, where 1 refers to very low happiness, and 50 signifies extreme happiness.  The population mean for “work happiness” on this scale is 25, but you don’t have access to the population standard deviation. Your analysis will examine happiness differences between the company employees and the population. You predict the employees will show a higher work happiness score than the population. You randomly recruit 30 employees from the 250, and they all agree to complete the Happiness at Work Scale at the organisation’s head office on a Friday morning.  The data you collect from the 30 participants is shown in Table 1. Task 1 (1) Write a results section (“draft answer”). 1 mark for this “working out” (2) What is the name of the statistical analysis you used? (3) What is the mean age of male and female participants? Female = Male  = (4) Which (if any) participant was an outlier? (Provide their ID number, or write “no outlier” if you didn’t identify anyone). (5) If there was an outlier, what number did you change their score to? (write “Not applicable” if there was no outlier). (6) Was the assumption of normality met? (Yes/No). (7) What were the degrees of freedom for the test statistic? (8) What wast?_he value of the test statistic? (9) What was the probability value associated with the test statistic?  (use “p < 0>TASK 2 Circle the number next to the statement which most accurately summarises the research findings. (1) The mean happiness rating of the sample was significantly higher than the population mean. (2) The mean happiness rating of the sample was statistically equivalent to the population mean (3) The mean happiness rating of the sample was significantly lower than the population mean. (4) Not enough information provided to determine an answer. TASK 3 You’ve mistakenly allowed a single, obvious design flaw to potentially affect the validity of your results.  What is it? (only write a single word, phrase or short sentence; for example, “lack of reliability” or “experimenter effect”).

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