Central Tendency And Variability

CENTRAL TENDENCY AND VARIABILITY

CENTRAL TENDENCY AND VARIABILITY

Complete the following assignment by analyzing the provided data using SPSS. Ensure that all analyses are completed within SPSS, and include all relevant output and graphs in your submission. You will need to interpret the results, answer conceptual questions, and justify your conclusions based on statistical principles and the data outputs.

Paper For Above instruction

Your paper should begin with an introduction that contextualizes the importance of measures of central tendency and variability in psychological research. Follow this with detailed sections addressing each part of the assignment, including calculations, interpretations of SPSS outputs, and critical thinking about the data. Conclude with a summary of key insights gained from the analyses.

Part I: Concepts Questions

1. Fill in the blank: The name for the middle score in a sample when the scores are arranged in ascending order is the median.

2. Fill in the blank: The letter that represents the total number of scores in a sample is N.

3. Fill in the blank: The measure of central tendency most likely to be negatively affected by outliers is the mean.

4a. Using the provided scores for eleven patients on the Beck Depression Inventory (BDI), compute the mean. The scores are: [Insert scores if available].

4b. Determine the median of these scores.

5a. Using the interactive NYC income graph, identify the borough with the highest median household income on Line 7.

5b. In Queens (QNS), identify the subway stop that appears as an outlier compared to the others and explain why.

5c. On Line 2, which borough shows the least variability in median household income?

5d. Considering the median incomes at the first and last stops on Line 2, assess whether the income along the line is stable and low in variability.

5e. Explain why the author chose the median household income instead of the mean for this graph.

Part II: SPSS Analysis

Using the data set from the American Time Use Survey, perform the following analyses:

  1. Create a histogram for the variable SLEEP and paste it into your document.
  2. Compute descriptive statistics for EATDRINK using the Explore method and include the table.
  3. Construct a histogram for EATDRINK and include it.
  4. Generate a Descriptives table for LAUNDRY by GENDER, displaying separate statistics for each group.
  5. Describe the shape of the distribution for SLEEP based on the histogram.
  6. Report the skewness value for EATDRINK from your SPSS output.
  7. Evaluate whether the histogram of EATDRINK suggests a ceiling or floor effect, and explain your reasoning.

Part III: SPSS Data Entry and Analysis

Create a data file for the variable JOB_SEARCH_MINUTES:

  1. Start a new SPSS dataset and create a variable called “Job_Mins” as a scale measure.
  2. Enter the provided data points into the variable.
  3. Compute descriptive statistics using the Explore method and paste the resulting table.
  4. Create a histogram of Job_Mins and include it.
  5. Report the mean, median, and skewness based on your SPSS output.
  6. State which measure of central tendency (mean or median) best describes this data and justify your choice.

Part IV: Cumulative Questions

1. Using SPSS, run a frequencies analysis on the BDI scores. Insert the frequency table into your document.

2. What percentage of the sample has a BDI score of 11?

Ensure all graphs, tables, and written responses are included in your homework file. Your analysis should be thorough, interpretation accurate, and justifications clear.

References

  • Brace, N., & Snelgar, R. (2016). SPSS for psychological research. Sage Publications.
  • Field, A. (2013). Discovering statistics using IBM SPSS statistics. Sage.
  • Gravetter, F. J., & Wallnau, L. B. (2017). Statistics for the behavioral sciences. Cengage Learning.
  • Heathcote, A., et al. (2019). Quantitative psychology and statistics with SPSS. Routledge.
  • IBM Corp. (2023). IBM SPSS Statistics for Windows, version 28.0. IBM Corp.
  • Tabachnick, B. G., & Fidell, L. S. (2018). Using multivariate statistics. Pearson.
  • Tabachnick, B. G., & Fidell, L. S. (2013). Using multivariate statistics (6th ed.). Pearson.
  • Wilkinson, L., & Task Force on Statistical Power. (2014). Statistical methods in psychology journals: Guidelines and explanations. American Psychologist.
  • Coakes, S. J., & Steed, L. G. (2019). Analysis without anguish: SPSS version 26. John Wiley & Sons.
  • Field, A., Miles, J., & Field, Z. (2012). Discovering statistics using R. Sage.

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