PSYC 354 Homework 2: Frequency Tables And Graphs When Submit

PSYC 354 Homework 2 Frequency Tables and Graphs When submitting this file, be sure the filename includes your full name, course and section.

Answer all questions in the spaces provided.

Complete all analyses in SPSS, then copy and paste your output and graphs into your homework document file. Answer any written questions (such as the text-based questions or the APA Participants section) in the appropriate place within the same file.

Part I: Concepts

  1. The following table depicts exam scores for a group of 65 students. Use the information in the table to determine the percentages for each interval and the total frequency and percentage. Fill these into the blank boxes in the table. These may or may not add up to exactly 100% depending on rounding but should be very close.
  2. Scores that have not yet been transformed or analyzed are ___________ scores.
  3. ________ look like bar graphs but typically display scale data.
  4. A frequency distribution that is bell-shaped, symmetrical, and unimodal is ___________.
  5. A frequency distribution of ages of residents at an assisted living facility for the elderly is clustered around 82 with a long tail to the left. This distribution is ____________- skewed.
  6. When a constraint prevents a variable from taking on values above a certain point, this is known as a(n) ________ effect.
  7. A _________ depicts the relationship between two scale variables using dots.
  8. When graphing a nominal independent variable and a scale dependent variable, you could use a ________ or a _________.
  9. A line graph depicts the relationship between two _________ variables.
  10. Do the data in the scatterplot below show a linear relation, non-linear relation, or no relation at all? Answer
  11. Do the data in the scatterplot below show a linear relation, non-linear relation, or no relation at all? Answer

Part II: SPSS Analysis

Be sure you have viewed the SPSS tutorial presentation before proceeding.

- Open the “Module 2 Exercise File 1” in the course’s Assignment Instructions folder to complete these exercises.

- Paste all SPSS output and graphs into your homework file and write your answers in the spaces provided.

Questions 1-5

- Open Module 2 Exercise File 1. It contains data from the 2016 General Social Survey, with variables describing gender, marital status, region, political party, and religious preference.

- Variables include: SEX, MARITAL, REGION, POL_PARTY, REL_PREF. The data contains high categories due to options like “no answer,” “unknown,” or “undecided.”

  1. In SPSS, conduct a “Frequencies” analysis on the Marital Status variable. Paste the output; then, from the output, identify the following:
  • a. Percentage of married people
  • b. Most frequently occurring marital status (mode)
  • c. Frequency of people who are widowed in the sample
  • Run a Frequencies analysis to summarize the data on the Political Party variable. Paste the table.
  • Create a pie chart summarizing the Political Party data. Paste the chart.
  • Create a bar chart showing Religious Preference. Use the “Summaries of Groups of Cases” method. Paste the chart.
  • Write an APA-style Participants section describing the demographic characteristics of the sample based on the data collected.

    • Part III: SPSS Data Entry and Analysis

    Follow the steps below to create your own data file:

    • Name and define variables in “Variable View.”
    • Return to “Data View” to enter data.
    • Paste all SPSS output and graphs into your homework file appropriately.

    Questions 1-3

    1. Research scenario: A psychologist studies how recent substance use affects reaction time. Data include substance type and reaction time.
    2. Create two variables: “SubAbuse” (nominal) and “ReacTime” (scale).
    3. Define “SubAbuse” values as 1=Alcohol, 2=Opioid, 3=Marijuana, 4=Cocaine. Enter the provided data.
    4. Create a bar chart for “SubAbuse.” Paste the chart.
    5. Create a histogram for “ReacTime.” Paste the histogram.
    6. Explain why a bar chart is suitable for “SubAbuse” and a histogram for “ReacTime,” focusing on their X axes.

    Submit Homework 2 by 11:59 p.m. (ET) on Monday of Week 2. Be sure to name your file appropriately.

    Paper For Above instruction

    Based on the instructions provided, this paper encompasses multiple sections including conceptual questions related to frequency distributions and graphs, analysis of survey data using SPSS, and practical data entry and visualization exercises within SPSS. It demonstrates understanding of statistical concepts, proficiency in data analysis tools, and skills in reporting demographic and research data following APA standards.

    Understanding frequency tables and their components is fundamental in descriptive statistics. For instance, when analyzing exam scores for a group of 65 students, calculating percentages for score intervals involves dividing the frequency of each interval by the total number of students and multiplying by 100 to obtain the percentage. These percentages may slightly vary from a perfect 100% due to rounding conventions but should be very close. Such tables enable researchers to visualize the distribution of scores, identify modes, and observe skewness or symmetry in the data.

    Scores that have yet to undergo transformation or analysis are typically called raw scores. These represent the original data collected before any statistical modifications, such as standardization or categorization. Recognizing raw data is vital as it forms the basis for meaningful analysis and subsequent interpretation.

    Graphs such as histograms and bar graphs serve different purposes despite superficial similarities. Histograms are suitable for displaying frequency distributions of scale (interval or ratio) data, with the X-axis representing continuous values which are grouped into bins. Bar graphs, however, are preferable for nominal or categorical data, where the X-axis denotes distinct categories without a specific order. This distinction underpins why histograms are used for reaction times, a continuous scale, and bar graphs for categorical variables like substance use or marital status.

    A frequency distribution that appears bell-shaped, symmetrical, and unimodal typifies a normal distribution. Such distributions are significant because many statistical tests assume normality, and understanding their properties helps analysts evaluate data quality and suitability for parametric tests.

    Skewness describes the asymmetry in a distribution. A distribution clustered around 82 years with a long tail to the left indicates a negative skewness. Such skewness often results from a few unusually young ages in an elderly age distribution, which pulls the tail leftward, while most data points cluster around the central value.

    The concept of a constraint restricting a variable from exceeding a certain upper limit is termed a ceiling effect. This phenomenon can lead to issues in data analysis, as it artificially truncates data, limiting variability and potentially biasing results.

    Scatterplots are statistical graphics that depict the relationship between two scale variables. Each point represents the values of the variables for a single observation, allowing visual assessment of correlation, linearity, or non-linearity.

    Graphing relationships between a nominal independent variable and a scale dependent variable can be accomplished using bar charts or boxplots. These visuals facilitate comparison across categories to identify differences or patterns in the dependent variable's distribution.

    Line graphs are primarily used to represent the relationship between two continuous variables, especially when illustrating how one variable changes in relation to another over a continuum.

    In analyzing scatterplots, a visual pattern indicating linearity suggests that the relationship between variables can be described with a straight line. Non-linear patterns may resemble curves or other shapes, indicating more complex relationships, while a lack of any discernible pattern suggests no relation.

    The SPSS analysis involves conducting frequency analyses, creating visualizations such as pie charts and bar charts, and writing demographic descriptions consistent with APA format. The exercises reinforce skills in data organization, descriptive statistics, and graphic presentation, essential for psychological research.

    The hands-on task of creating new variables in SPSS, such as “SubAbuse” and “ReacTime,” involves defining measurement levels and inputting data, which demonstrates practical data management. Selecting suitable graphs—bar charts for categorical data and histograms for continuous data—reflects an understanding of appropriate visualization techniques, critical for correct data interpretation.

    References

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