Assessment 1
provides three research scenarios, each with associated numerical data and tasks to complete. For each scenario you are to assume the role of a researcher employed by an organisation with the purpose of helping them answer a question about their business. Your role is to analyse the data using SPSS and answer the questions provided.
Each scenario consists of three tasks:
TASK 1:
– Analyse the data provided using the relevant statistical analysis in SPSS, and correctly answer questions concerning;
– The hypothesis (including the units of measure for the dependent variable)
– The overall number of participants and the means and standard deviations of the age of these participants, grouped by sex.
– Parametric assumptions
– The correct presentation of the statistical findings
– Any post-hoc analyses (if appropriate)
– Effect sizes (if appropriate)
TASK 2:
Accurately interpret the research findings
. TASK 3:
Identify whether an experimental design flaw exists in the scenario. Correctly determine how the flaw (if it exists) might affect the statistical finding leading to an inaccurate or invalid conclusion.
Length: 1,000 words
Curriculum Mode: Report
/Assessment instructions
Assessment 1 contains THREE research scenarios. For each scenario, you are assuming the role of a researcher (employed by various commercial and government organisations) for the purpose of helping them find solutions to questions they have about their business practice.
Each scenario is worth 20 marks (meaning the overall assessment is out of 60, which is then divided by 2 to total 30% of the units mark).
Each scenario consists of THREE tasks, detailed as follows;
TASK 1: Draft results and associated questions
For Task 1 in each scenario, analyse the data provided in the table using the relevant statistical technique (using SPSS, or perhaps even by handif a ztest is appropriate).Read the scenario carefully – the analysis required will be either a onesample ztest, a one sample ttest, a dependent samples ttest, an independent samples ttest or a oneway ANOVA, or their nonparametric equivalents (and because there are only three scenarios, some of the analysis styles youve learned about will not be applicable to this assessment).As a first step, use the etutorial demonstration exercises, etopics, and the relevant resultsexemplar in the foolproof guide (e.g., for an independent samples ttest) to help you write a DRAFT results section incorporating your statistical findings. This draft results section will contain the necessary statistical values required to answer subsequent specific questions (and can be anywhere between 150 and 300 words, depending on the analysis you use; simply use as many words as you require to successfully complete the draft based on the class exemplar).In the draft results you should include;
1. An opening sentence describing the hypothesis.
2. Participant number, mean age and standard deviation of age.Make sure you provide the number of participants IN EACH GROUP. This is straightforward if you are performing a ztest, onesample ttest, dependent samples ttest, or Wilcoxon Ttest, because there is only one group of participants. You should report the number of females and males for each group and calculate means and standard deviations of the age of males and females separately for each group.However, be aware there will be two groups for an independent samples ttest or MannWhitney U test, and three or more groups for ANOVA or KruskalWallis.So, for example, if the scenario involves two groups of participants (i.e., two levels of the IV, for example an independent samples ttest), for GROUP 1 calculate the number of females, their mean age and standard deviation; then calculate the number of males, their mean age andstandard deviation. Then for GROUP 2, calculate the number of females, their mean age and standard deviation and separately the number of males, their mean age and standard deviation.(Hint: if you find participants with missing data, remove them completely from the data before you perform any analysis, including mean age and number of participants).
3. Tests of parametric assumptions (outliers and normality)OUTLIERSInvestigate outliers separately for each group, if you identify a betweendesign is used. For a withindesign, investigate outliers for each level of the independent variable (e.g., if it is a beforeandafterrepeated measures design, test outliers separately for the before data set, and for the after data set).If you do discover (and then change) an outlier for a data set, you do not have to rerun the outlier analysis again to find more. One analysis is enough!NORMALITYFor onesample z and ttests, theres only one column of data for the single group, so you only need to perform a single normality test.For a dependent samples ttest involving two columns of data for each participant, examine normality for each column separately.Test
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