Data Analysis and Application (DAA) TemplateUse this file for all assignments that require the DAA Template. Although the statistical tests will change from assessment to assessment, the basic...

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Data Analysis and Application (DAA) Template





Use this file for all assignments that require the DAA Template. Although the statistical tests will change from assessment to assessment, the basic organization and structure of the DAA remains the same.







Update the title of the template. All should be written in narrative form (delete numbered lists).














Data Analysis Plan








  1. Name the variables and the scales of measurement.



  2. State your research question, null and alternate hypothesis.











Testing Assumptions








  1. Paste the SPSS output for the given assumption.



  2. Summarize whether or not the assumption is met.











Results and Interpretation








  1. Paste the SPSS output for main inferential statistic(s) as discussed in the instructions.





  2. Interpret statistical results as discussed in the instructions.









Statistical Conclusions








  1. Provide a brief summary of your analysis and the conclusions drawn.



  2. Analyze the limitations of the statistical test.





  3. Provide any possible alternate explanations for the findings and potential areas for future exploration.











Application








  1. Think of your own field of study. Describe how this type of analysis might be used in your field.





  2. Analyze what the value and potential implication of such an analysis would be.









References




Provide references in proper APA Style.




JASP Step-by-Step: Correlations di IJASP • • ILi lll. ~ l!!C Descriptives T-Tests ANOVA Mixed Models Regression Frequencies "' Descriptive Statistics 0 0 0 0 ' id I~ Variables A, tastname A fi rstname I genderidentity 1d ethnicity I year A lowup 111 section ' gpa A extcr A review I quiz.1 ,d qu;z2 I quiz3 ,d quiz.4 I quiz5 Split , fin al ► Transpose descriptives table ► ► statistics ► Basic plots ► Customizable plots ► Tables • ______________________________________________________________________________ Correlations DAA Section 2: Testing Assumptions Open grades.jasp. Section 2 asks for a test of the normality assumption. Select the Descriptives option from the menu bar and a new window appears. Select quiz1. Select the arrow to move quiz1 to the Variables box. SCREENSHOTS TAKEN FROM JASP version 16. T Descriptive Statistics 0 0 0 0 A id !~ I Variables I & lastname ► & firstname A genderidentity A ethnicity 1d year A lowup A section ' gpa A extcr A quiz3 quiz4 quiz5 .Split , final ► •• • T Descriptive Statistics 0 0 0 0 I Variables I A id !~ & lastname ► quiz 1 & firstname A genderidentity A ethnicity 1d year A lowup A review quiz2 quiz3 quiz4 quiz5 , final Split , total ► II Select gpa. Select the arrow to move gpa to the Variables box. e ... Descriptive Statistics 0 0 0 0 A id J¢: Variables I;., lastname ► quiz1 I;., firstname ' gpa A gen deri dentity A ethnicity I year A lowup A section A extcr A review , quiz2 , quiz3 ' quiz4 ' quiz5 , final Split ► e ... Descriptive Statistics G O O 0 A id 1¢: j variables j &, lastname ► quiz1 &, firstname ' gpa A gen deridentity , Iota.I A ethnicity I year A lowup A section A extcr Split ► Select total. Select the arrow to move total to the Variables box. Select final. Select the arrow to move final to the Variables box. ... Descriptive Statistics ,. id ._, lastnarn e ._, firstrn arn e ,. genderi dentity ,. ethnicity I year ,. lowup ,. section ,. extcr ,. review ' quiz2 ' quiz3 ' quiz4 ' quiz5 percent ._, grade ,. passfail Transpose descriptives table ► Statistics e T Stati stics Sample size Vali d Missing Central ten den cy Mode Median Mean Dispersion S.E. mean I~ Coefficient of vari ation MAD ro bust Variance Minimum ► ► Quantiles Quartiles Variables ' quiz1 ' gpa ' total , final Split Cut points for: 4 Distrib PJ Skewness Kurtosis Sid. deviation MAD !QR Range Maximum 0 0 0 0 11 equal groups Select the Statistics button. New options appear. Select Skewness and Kurtosis. (Deselect other options). 8 • Descriptiive Statistiics Skewness s· d. Error o Skew11ess Kurtosis S d. Error of Kmtosils . Q;lliz1 grad es ((!:\ U sers\ swowr\ On eDrive\ Desktop) - Dese:niptives T-i'ests AJNOVA • gpa to I 'I' ..,. Mixed Models final Logisti c Reg ression Generalized Linear Model __________________________________________________________ Copy/paste the Descriptive Statistics table into DAA Section 2. Below the output, discuss the skewness and kurtosis values and how you determined whether the assumption of normality was met or violated. DAA Section 3: Intercorrelation Matrix Section 3 asks for the intercorrelation matrix. Select Regression from the toolbar. Select Classical Correlation; a new window appears. Select quiz1. Select the arrow to move quiz1 to the Variables box. T Correlation gpa extcr quiz3 Quiz4 quiz5 , final Sample Correlation Coefficient fJ Pearson's r Spearman's rho Kendall's tau-b e T Correlation llfi) 1111::>UIC:Hllt:! A genderidentity A ethnicity id year A IOWJP A review quiz2 Sample Correlation Coefficient fJ Pearson's r Spearman's rho Kendall's tau-b !~ Variables ► Partial out ► Additional Options Display paiiwise fJ Report significance Flag significant correlations Confidence inteivals Variables ► , Quiz1 Partial out ► Additional Options Display paiiwise fJ Report significance Flag significant corre ations Confidence inteivals 0 0 0 0 0 0 0 0 , .. Select gpa. Select the arrow to move gpa to the Variables box. Select total. Select the arrow to move total to the Variables box. "' Correlation - IUWUIJ A section A extcr A review , Quiz2 , Quiz3 ' ' Sample Correlation Coefficient II Pearson's r • Spearman's rho Kendall's tau-b "' Correlation -IUWUIJ A section A extcr A review ' Quiz2 ' Quiz3 ' ' Sample Correlation Coefficient II Pearson's r Spearman's rho Kendall's tau-b • 1~ ► ► Variables , Quiz1 ' gpa Partial out Additional Options Display paiiwise II Report significance Flag significant correlations Confidence intervals Variables ► , Quiz1 ' gpa , total Partial out ► Additional Options Display paiiwise II Report significance Flag significant correlations Confidence intervals 0 0 0 0 0 0 0 0 •• Select final. Select the arrow to move final to the Variables box. Select Flag significant correlations. • T Correlation 1U yecu ,. lowup ,. section ,. extcr ,. review ' quiz2 ' quiz3 ' quiz4 ' quiz5 , percent Sample Correlation Coefficient S Pearson's r Spearman's rho Kendall's tau-b Correlation Pearson's Correlations Variable 1. quiz 1 Pearson's r p-value 2. gpa Pearson's r p-value 3. total Pearson's r p-value 4. final Pearson's r p-value !~ * p < .05,="" **="" p="">< .01,="" ***="" p="">< .001="" •="" variables="" ►="" ,="" quiz1="" '="" gpa="" total="" ""="" fin::il="" partial="" out="" ►="" additional="" options="" display="" paiiwise="" s="" report="" significance="" s="" flag="" significant="" correlations="" confidence="" intervals="" quiz1="" gpa="" total="" 0="" 0="" 0="" 0="" j="" ,="" ..="" final="" copy="" and="" paste="" the="" intercorrelation="" matrix="" into="" daa="" section="" 3.="" below="" the="" output,="" report="" the="" total-final="" correlation="" including="" degrees="" of="" freedom,="" correlation="" coefficient,="" and="" p="" value.="" specify="" whether="" or="" not="" to="" reject="" the="" null="" hypothesis="" for="" this="" correlation.="" second,="" report="" the="" gpa-quiz1="" correlation="" including="" degrees="" of="" freedom,="" correlation="" coefficient,="" and="" p="" value.="" specify="" whether="" or="" not="" to="" reject="" the="" null="" hypothesis="" for="" this="" correlation.="" daa="" sections="" 2="" and="" 3="" should="" look="" like="" this="" page.="" descriptive="" statistics="" descriptive="" statistics="" quiz1="" gpa="" total="" final="" skewness="" std.="" error="" of="" skewness="" ■="" kurtosis="" std.="" error="" of="" kurtosis="" correlation="" pearson's="" correlations="" variable="" qui?1="" gpa="" total="" final="" 1.="" quiz="" 1="" pears:m's="" r="" p-,alue="" 2.="" gpa="" pears:m's="" r="" p-,alue="" 3.="" total="" pears:m's="" r="" o-,alue="" 4.="" fino.l="" pcor~jn'c="" r="" -o-,alue="" •="" p="">< .05.="" h="">< .01.="" •n="" o="">< .001 testing assumptions interpret the skewness and kurtosis values and how you determined whether the assumption of normality was met or violated. results & interpretation below the output, first report the total-final correlation including degrees of freedom, correlation coefficient, and p value. specify whether or not to reject the null hypothesis for this correlation. second, report the gpa-quiz1 correlation including degrees of freedom, correlation coefficient, and p value. specify whether or not to reject the null hypothesis for this correlation. correlations testing assumptions interpret the skewness and kurtosis values and how you determined whether the assumption of normality was met or violated. results & interpretation below the output, first report the total-final correlation including degrees of freedom, correlation coefficient, and p value. specify whether or not to reject the null hypothesis for this correlation. second, report the gpa-quiz1 correlation includin... .001="" testing="" assumptions="" interpret="" the="" skewness="" and="" kurtosis="" values="" and="" how="" you="" determined="" whether="" the="" assumption="" of="" normality="" was="" met="" or="" violated.="" results="" &="" interpretation="" below="" the="" output,="" first="" report="" the="" total-final="" correlation="" including="" degrees="" of="" freedom,="" correlation="" coefficient,="" and="" p="" value.="" specify="" whether="" or="" not="" to="" reject="" the="" null="" hypothesis="" for="" this="" correlation.="" second,="" report="" the="" gpa-quiz1="" correlation="" including="" degrees="" of="" freedom,="" correlation="" coefficient,="" and="" p="" value.="" specify="" whether="" or="" not="" to="" reject="" the="" null="" hypothesis="" for="" this="" correlation.="" correlations="" testing="" assumptions="" interpret="" the="" skewness="" and="" kurtosis="" values="" and="" how="" you="" determined="" whether="" the="" assumption="" of="" normality="" was="" met="" or="" violated.="" results="" &="" interpretation="" below="" the="" output,="" first="" report="" the="" total-final="" correlation="" including="" degrees="" of="" freedom,="" correlation="" coefficient,="" and="" p="" value.="" specify="" whether="" or="" not="" to="" reject="" the="" null="" hypothesis="" for="" this="" correlation.="" second,="" report="" the="" gpa-quiz1="" correlation="">
Answered 1 days AfterSep 08, 2023

Answer To: Data Analysis and Application (DAA) TemplateUse this file for all assignments that require the DAA...

Pratibha answered on Sep 10 2023
27 Votes
Statistical Analysis
Name of the student
Student ID
Variable Names and Scales of Measurement
Variable names and scales of measurement for the provided dataset:
    Variable
    Description
    Data type
    Id
    Unique identifier
    Nominal
    Lastname
    Last name of student
    Nominal
    Fisrtname
    First name of student
    Nominal
    Genderidentity
    Gender Identity (1 = Male, 2 = Female)
    Nominal
    Ethnicity
    Ethnicity (1 = Asian, 2 = Black, 3 = Hispanic, 4 = White)
    Ordinal
    Year
    Student Year
    Ordinal
    l
owup
    Lowup
    Ordinal
    section
    Section
    Ordinal
    Gpa
    GPA
    Continuous
    extcr
    External credits
    ordinal
    review
    Review session attended or not
    Ordinal
    Quiz1,quiz2,quiz3,
quiz4,quiz5
    Quiz Scores
    continuous
    Final
    Final exam score
    continuous
    total
    Total score
    continuous
    percent
    Percentage score
    continuous
    grade
    Grade (A,B, C,D)
    Nominal
    passfail
    Pass/Fail (1=Pass, 0=Fail)
    Nominal
Research Question and Hypotheses
Research Question: "What factors are associated with student performance and whether they pass or fail?"
· Null Hypothesis ($H_0$): "There is no significant relationship between the independent variables (e.g., gender, ethnicity, GPA) and student performance (pass/fail)."
· Alternate Hypothesis ($H_A$): "There is a significant relationship between the independent variables and student performance."
For testing the relationship between independent variables (e.g., gender, ethnicity, GPA) and student performance (pass/fail), we can use a chi-squared test of independence. This test is appropriate when you have categorical independent variables and a categorical dependent variable like "pass/fail." Specifically, we can perform a chi-squared test for independence or a chi-squared test for association.
Testing Assumptions:
The chi-square test of independence has some assumptions that need to be considered when applying it to a dataset. These assumptions are related to the nature of the data and the appropriateness of the test. Here are the key assumptions for the chi-square test of independence:
1. Independence of Observations: The observations in the contingency table (cross-tabulation) should be independent of each other. In other words, the data points should not be influenced by or dependent on each other. Violations of this assumption can lead to inaccurate results.
2. Random Sampling: The data should come from a random sample or a well-defined sampling process. This ensures that the sample is representative of the population from which it was drawn.
3. Expected Cell Frequencies: The expected cell frequencies (the values that would be expected under the null hypothesis of independence) should be greater than or equal to 5 for most cells in the contingency table. This assumption is known as the "5 or more" rule.
4. If the expected cell frequencies are very small (less than 5), the chi-square test may not be appropriate, and alternative tests (e.g., Fisher's Exact Test) should be considered.
5. Categories are Mutually Exclusive: The categories or levels of the categorical variables should be mutually exclusive, meaning that each observation should belong to only one category.
6. Ordinal or Nominal Data: The chi-square test is most appropriate for categorical data that is either ordinal (categories have a natural order) or nominal (categories have no natural order).
7. Large Sample Size: While the chi-square test is robust to violations of normality assumptions, it is more reliable with larger sample sizes. Small sample sizes can lead to less reliable results.
Results and Interpretation

The descriptive statistics presented summarize various characteristics of a dataset containing 105 valid data points across multiple variables. Here's a detailed summary of the key findings:
· The dataset appears to include a mix of categorical and numerical variables. Among the numerical variables, the mean GPA stands at 2.862, indicating an average academic performance. The "total" variable, with a mean of 61.838, suggests a scoring system or total points, and the "percent" variable has a mean of 100.086, possibly representing percentages.
· The categorical variables include "genderidentity" and "ethnicity," with means of 1.714 and 3.352, respectively. These values likely correspond to categories or codes representing gender identity and ethnicity, but the specific interpretations would require additional context.
· The dataset includes several "quiz" variables (quiz1 to quiz5), each with mean values around 7.5, indicating relatively consistent quiz scores. The "passfail" variable has a mean of 0.543, suggesting that the majority of observations fall within one category.
· Standard errors, confidence intervals, and standard deviations provide information about the precision of the mean estimates and the variability in the data.
· The Shapiro-Wilk tests indicate that some variables deviate from a normal distribution, as reflected in their small p-values.
· In conclusion, these descriptive statistics offer insights into the central tendency, variability, and...
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