Long Answer

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OverviewSubmita single word-processed document using appropriateword-processingsoftware (e.g., Word, LibreOffice, LATEX,R Markdown).Embedall imagesin the document.Please submit the document in.doc, .docx, .odt, or.pdf file format (.pdf is preferred). Submit the documentusing the Final Assignmentsubmission portal on the course eClass page.All data required to complete the assignment are available intextformatthroughout this document.To aid students who opt to use statistical software, all the text-formatted data in thisdocument have been duplicated into a series of .csv files also located intheFinal Assignment folder.Each .csv file is intuitively labeled according to the Long Answer question for which it is intended(e.g., file “Q1.csv” contains the data for Long Answer question 1).Long Answer(70marks)For these questions, you are given brief summaries of research scenarios,specific hypotheses, andaccompanying data.You are required toconduct appropriate statistical analyses of the datato draw conclusions for eachresearch hypothesis.Write a brief reportof the results in which you •Highlightall inferential statistical effects (e.g., There was astrongmain effect of Factor A)•Discussthe qualitative nature of any such effects (e.g., Group A scored higher on <dependent variable>than group B)•Report the results of your statistical tests using the appropriate APA formatting for each respective statistical test(e.g., t[12] = 2.53, p= .026, d= 0.74, 95% CI = [1.34, 4.78])•Refer back to the research scenario tomake a broad declarative statement abouthow well the research hypothesis issupportedFor all analyses, assume two-tailed hypothesis tests with ?= .05 unless otherwise specified. All parametric analyses must includeeffect sizes.Any t-tests must include95% confidence intervals. Any analysis that includes an F-test must also include an accompanying ANOVA table. Any analysis that includes a correlation must also include the variances of the variables and their cross product (SP; covariability). Anyanalysis that includes linear regression must also include all relevant descriptive statistics (i.e., SSResidual,standard error of the residual, regression equation).Any non-parametric analysismust include the ranked scores and the sum of ranks (?R).You are free to use statistical software (e.g., SPSS, SAS, R, sciPy, MATLAB)to conduct statistical analysesand construct data plots. However, you must provide screenshots of your outputas part of your submission. Please embed theseimages in the word-processed document, rather than submitting them separately.If you would prefer to compute

2statistical tests and construct data plots by handon paper,please take photos of your work and embed them intoyour submission in much the samemanner. Alternatively, you could type out your hand calculations, but this would likely be rather tediousand wethereforeadvise against it.If you opt to use statistical software, please report exact pvaluesfor each statistical test(e.g., p= .026).Otherwise, if you perform hand calculations, report pvalues in relation to (e.g., less than) the appropriate ?-level (e.g., ?= .05) and include the critical values from the relevantstatistical tables provided in the textbookfor each statistical test(e.g., p< .05; tcrit= 2.18).Question 1(24 marks)A human-computer interaction (HCI) researcher was interested in examining whether humans are better able to use a joystickor a mouse to pointa computer cursor.She therefore constructed an experiment in which participants usedeither a joystick (joystickcondition) or a mouse (mousecondition) to pointa cursor to a target displayed on a computer monitor.She measured the time (seconds)that it took to place the cursor overthe target (dependent variablereferred to astime,wherea higher timescore indicates poorer performance). To determine whether potential benefits of usingthe joystick or mouse generalized to difficult HCIscenarios, the target was either stationary (staticcondition)or moved slowly across the computer screen at a constant velocity (motioncondition).Participants were randomly and uniquely assigned to 1 of 4 conditionsinthe interface(levels: joystick, mouse)×target type(levels: static, motion) experimental design.Given the data collected by the researcher (see Table 1 below), what can she conclude about how easily humans interact these HCIinterfaces and how are theseHCI interfacesinfluenced by target type?Include a line graphof the means.