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PSY-FP7864 – Section 02

[u01a1] – Histograms and Descriptive Statistics

Moore , Ashley

Use the following scoring guide, along with the project information, for evaluating each learner’s work.

Assessment Instructions

Preparation

This assessment has three parts, each of which is described below. Submit all three parts as Word documents.

Note: All the course documents you will need for the assessment are linked in the Resources section.

Read Assessment 1 Context to learn about the concepts used in this assessment.

This assessment uses the grades.sav file, found in the Resources for this assessment.

The fictional data in the grades.sav file represent a teacher’s recording of student demographics and performance on quizzes and a final exam across three sections of the course. Each section consists of about 35 students (N = 105).

There are 21 variables in grades.sav. To prepare for this assessment, complete the following:

  • Open your grades.sav file and navigate to the “Variable View” tab.
  • Read the Data Set Instructions, and make sure you have the correct Values and Scales of Measurement assigned.

Part 1: Histograms and Descriptive Statistics

Your first IBM SSPS assessment includes two sections:

  • Create two histograms and provide interpretations.
  • Calculate measures of central tendency and dispersion and provide interpretations.

Key Details and Instructions

  • Submit your assessment as an attached Word document.
  • Begin your assessment by creating a properly formatted APA title page. Include a reference list at the end of the document if necessary. On page 2, begin Section 1.
  • Organize the narrative report with your SPSS output charts and tables integrated along with your responses to the specific requirements listed for that assessment. (See the Copy/Export Output Instructions in the Resources for instructions on how to do this.)
  • Label all tables and graphs in a manner consistent with APA style and formatting guidelines. Citations, if needed, should be included in the text as well as a reference section at the end of the report.
  • For additional help in completing this assessment, refer to IBM SPSS Step-By-Step Instructions: Histograms and Descriptive Statistics, linked in the Resources.

Section 1: Histograms and Visual Interpretation

Section 1 will include one histogram of “total” scores for all the males in the data set, and one histogram of “total” scores for all the females in the data set.

Create two histograms using the total and gender variables in your grades.sav data set:

  • A histogram for male students.
  • A histogram for female students.

Below the histograms, provide an interpretation based on your visual inspection. Correctly use all of the following terms in your discussion:

  • Skew.
  • Kurtosis.
  • Outlier.
  • Symmetry.
  • Modality.

Comment on any differences between males and females regarding their total scores. Analyze the strengths and limitations of visually interpreting histograms.

Section 2: Calculate and Interpret Measures of Central Tendency and Dispersion

Using the grades.sav file, compute descriptive statistics, including mean, standard deviation, skewness, and kurtosis for the following variables:

  • id.
  • gender.
  • ethnicity.
  • gpa.
  • quiz3.
  • total.

Below the Descriptives table, complete the following:

  • Indicate which variable or variables are meaningless to interpret in terms of mean, standard deviation, skewness, and kurtosis. Justify your decision.
  • Next, indicate which variable or variables are meaningful to interpret. Justify your decision. For meaningful variables, specify any variables that are in the ideal range for both skewness and kurtosis.
  • Specify any variables that are acceptable but not excellent.
  • Specify any variables that are unacceptable. Explain your decisions.
  • For all meaningful variables, report and interpret the descriptive statistics (mean, standard deviation, skewness, and kurtosis).

Part 2: Data Screening

For this part of the assessment, respond to the following questions:

What are the goals of data screening? How can you identify and remedy the following?

  • Errors in data entry.
  • Outliers.
  • Missing data.

Part 3: z Scores, Type I and II Error, Null Hypothesis Testing

This IBM SPSS assessment includes three sections:

  • Generate z scores for a variable in grades.sav and report/interpret them.
  • Analyze cases of Type I and Type II error.
  • Analyze cases to either reject or not reject a null hypothesis.

The format of this assessment should be narrative with supporting statistical output (table and graphs) integrated into the narrative in the appropriate place (not all at the end of the document). See the Copy/Export Output Instructions for instructions on how to do this.

Download the z Scores, Type I and Type II Error, Null Hypothesis Testing Answer Template from the Required Resources, and use the template to complete the following sections:

  • Section 1: z Scores in SPSS.
  • Section 2: Case Studies of Type I and Type II Error.
  • Section 3: Case Studies of Null Hypothesis Testing.

Overall Comments

Ashley, you did a good job with Part 2 of this assessment, but Part 1 is missing. Please read the instructions, complete this part, and let me know if you have any questions.

Lorie

Criterion

Non-performance

Basic

Proficient

Distinguished

Criterion

Apply the appropriate SPSS procedures for creating histograms to generate relevant output.

(9%) Competency

Apply a statistical program’s procedure to data.

selected Non-performance Does not provide SPSS output. not selected Provides SPSS output with errors. not selected Applies the appropriate SPSS procedures for creating histograms to generate relevant output. not selected Analyzes the histogram output, demonstrating insight and understanding of relevant data.

Comments:

I don’t see the histograms.

Criterion

Interpret histogram results, including concepts of skew, kurtosis, outliers, symmetry, and modality.

(9%) Competency

Interpret the results of statistical analyses.

selected Non-performance Does not provide an interpretation of histogram results. not selected Provides an interpretation of histogram results. not selected Interprets histogram results, including concepts of skew, kurtosis, outliers, symmetry, and modality. not selected Evaluates histogram results, including concepts of skew, kurtosis, outliers, symmetry, and modality.

Comments:

This is missing.

Criterion

Analyze the strengths and limitations of examining a distribution of scores with a histogram.

(9%) Competency

Analyze the computation, application, strengths, and limitations of various statistical tests.

selected Non-performance Does not identify the strengths and limitations of examining a distribution of scores with a histogram. not selected Identifies the strengths and limitations of examining a distribution of scores with a histogram. not selected Analyzes the strengths and limitations of examining a distribution of scores with a histogram. not selected Evaluates the strengths and limitations of examining a distribution of scores with a histogram. Demonstrates insight and understanding of relevant data.

Comments:

This is missing.

Criterion

Apply the appropriate SPSS procedure for generating descriptive statistics to generate relevant output.

(9%) Competency

Apply a statistical program’s procedure to data.

selected Non-performance Does not provide SPSS output. not selected Includes some, but not all, of the required output. Numerous errors in SPSS output. not selected Applies the appropriate SPSS procedure for generating descriptive statistics to generate relevant output. not selected Applies the appropriate SPSS procedure for generating descriptive statistics to generate relevant output. Includes all relevant output; no irrelevant output is included. No errors in SPSS output.

Comments:

This is missing.

Criterion

Analyze meaningful versus meaningless variables reported in descriptive statistics.

(9%) Competency

Analyze the decision-making process of data analysis.

selected Non-performance Does not identify meaningful versus meaningless variables reported in descriptive statistics. not selected Identifies meaningful versus meaningless variables reported in descriptive statistics. not selected Analyzes meaningful versus meaningless variables reported in descriptive statistics. not selected Evaluates meaningful versus meaningless variables reported in descriptive statistics.

Comments:

This is missing.

Criterion

Interpret descriptive statistics for meaningful variables.

(9%) Competency

Interpret the results of statistical analyses.

selected Non-performance Does not identify meaningful variables. not selected Identifies meaningful variables. not selected Interprets descriptive statistics for meaningful variables. not selected Evaluates descriptive statistics for meaningful variables.

Comments:

This is missing.

Criterion

Apply the appropriate SPSS procedures for creating z scores and descriptive statistics to generate relevant output.

(9%) Competency

Apply a statistical program’s procedure to data.

not selected Does not provide SPSS output. not selected Provides SPSS output with errors. not selected Applies the appropriate SPSS procedures for creating z scores and descriptive statistics to generate relevant output. selected Distinguished Analyzes the z scores and descriptive statistics output, demonstrating insight and understanding of relevant data.

Comments:

Good job using SPSS to calculate the z scores.

Criterion

Analyze the relevant data from the computation, interpretation, and application of z scores.

(9%) Competency

Analyze the computation, application, strengths, and limitations of various statistical tests.

not selected Does not identify the relevant data or generate output. selected Basic Identifies the relevant data and generates output. not selected Analyzes the relevant data from the computation, interpretation, and application of z scores. not selected Evaluates the relevant data from the computation, interpretation, and application of z scores. Justifies the meaningfulness of selected variables.

Comments:

The answer for Question 2 is incorrect. The percentile ranks for Questions 5 and 6 are incorrect.

Criterion

Analyze real-world application of Type I and Type II errors, and the research decisions that influence the relative risk of each.

(9%) Competency

Analyze the computation, application, strengths, and limitations of various statistical tests.

not selected Does not describe a real-world application of Type I and Type II errors and the research decisions that influence the relative risk of each. not selected Describes, but does not analyze, a real-world application of Type I and Type II errors and the research decisions that influence the relative risk of each. selected Proficient Analyzes a real-world application of Type I and Type II errors and the research decisions that influence the relative risk of each. not selected Evaluates real-world application of Type I and Type II errors and the research decisions that influence the relative risk of each.

Comments:

Good job overall! For Question 9, you say “A Type I error would speak to the dismissal that the new medication has turned out to be effective for depression treatment”. That might not be an error at all. If the drug doesn’t work then the researcher should dismiss it as effective for depression. It’s only an error if it either doesn’t work and the researcher says it does or if it does work (Type I error) and the researcher claims it doesn’t (Type II).

Criterion

Apply the logic of null hypothesis testing to cases.

(9%) Competency

Analyze the decision-making process of data analysis.

not selected Does not apply the logic for null hypothesis testing. not selected Inconsistently applies the logic for null hypothesis testing. selected Proficient Applies the logic of null hypothesis testing to cases. not selected Analyzes the logic of null hypothesis testing. Demonstrates insight and understanding of relevant data to either reject or not reject the null hypothesis.

Comments:

Good job with Question 10! For QUestion 11, you didn’t answer whether or not the researcher in this situation made and error, and if so which one. For Question 12, you say “we reject null hypothesis. Because the probability of that certain event occurring is very low.” You should say that the probability of a certain event occurring by chance is very low.

Criterion

Communicate in a manner that is scholarly, professional, and consistent with expectations for members of the identified field of study.

(10%) Competency

Communicate in a manner that is scholarly, professional, and consistent with the expectations for members in the identified field of study.

not selected Does not communicate in a manner that is scholarly, professional, and consistent with the expectations for members in the identified field of study. not selected Inconsistently communicates in a manner that is scholarly, professional, and consistent with the expectations for members in the identified field of study. not selected Communicates in a manner that is scholarly, professional, and consistent with the expectations for members in the identified field of study. selected Distinguished Communicates in a manner that is professional, scholarly, and consistent with expectations for members of the identified field of study. Adheres to APA guidelines, and work is appropriate for publication.

Comments:

Good job!

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