7.4 Data Analysis

    Cards (46)

    • Quantitative data is collected through interviews and observations.
      False
    • Standard deviation is a measure of how spread out the values are from the mean
    • What is the primary purpose of inferential statistics?
      Determine statistical significance
    • Inferential statistics allow researchers to draw conclusions about a broader population.
      True
    • Inferential statistics allow researchers to make conclusions about a broader population
    • Examples of inferential statistics include t-tests, ANOVA, and regression
    • Match the data type with its characteristics:
      Quantitative Data ↔️ Numerical and measured statistically
      Qualitative Data ↔️ Non-numerical and describes experiences
    • The mean is the average value, while the median is the middle value
    • If the p-value is below the threshold, the researcher can reject the null hypothesis
    • Inferential statistics allow researchers to make conclusions about a broader population.
      True
    • Examples of descriptive statistics include the mean, median, and standard deviation
    • A bar chart could display mean scores, while a table could summarize key themes
    • A study rejects the null hypothesis if the p-value is below 0.05
    • What is quantitative data in psychology?
      Numerical information
    • Match the type of data with its characteristic:
      Quantitative Data ↔️ Numerical
      Qualitative Data ↔️ Non-numerical
    • Descriptive statistics help researchers prepare data for further analysis.

      True
    • In hypothesis testing, researchers first state a null hypothesis
    • Match the type of statistics with its characteristic:
      Inferential Statistics ↔️ Uses hypothesis testing
      Descriptive Statistics ↔️ Summarizes sample data
    • Match the statistical approach with its primary purpose:
      Inferential Statistics ↔️ Make inferences about a population
      Descriptive Statistics ↔️ Summarize sample data
    • Best practices when creating data visualizations
      1️⃣ Use clear, informative titles and axis labels
      2️⃣ Select appropriate chart/table types
      3️⃣ Minimize clutter and extraneous elements
      4️⃣ Ensure color schemes are accessible
    • Quantitative data is numerical, while qualitative data is non-numerical
    • Standard deviation indicates the spread of data from the mean.

      True
    • Match the statistical approach with its primary purpose:
      Inferential Statistics ↔️ Make inferences about a population
      Descriptive Statistics ↔️ Summarize sample data
    • Match the type of statistics with its purpose:
      Inferential Statistics ↔️ Make inferences about a population
      Descriptive Statistics ↔️ Summarize sample data
    • Data visualization for quantitative data often involves charts
    • Well-designed visualizations enhance the impact and clarity of research findings.
      True
    • Confidence intervals provide a range within which the true population parameter is likely to fall.

      True
    • The p-value represents the probability that the observed results occurred by chance
    • Effect size measures the magnitude of an observed effect in standardized units.
    • A p-value of 0.03 and a Cohen's d of 0.7 indicate results that are statistically significant with a medium-to-large effect
    • Confidence intervals are typically set at a level of 95%
    • Qualitative data is non-numerical information describing characteristics, experiences, or behaviors
    • How is the mean calculated in descriptive statistics?
      Sum all values and divide
    • Match the descriptive statistic with its purpose:
      Mean ↔️ Indicates central tendency
      Range ↔️ Indicates variability
    • Steps involved in hypothesis testing
      1️⃣ State a null hypothesis
      2️⃣ Calculate a test statistic
      3️⃣ Determine the p-value
      4️⃣ Compare the p-value to a threshold
    • Steps in hypothesis testing in inferential statistics
      1️⃣ State the null hypothesis
      2️⃣ Calculate a test statistic
      3️⃣ Determine the p-value
      4️⃣ Compare the p-value to a threshold
      5️⃣ Decide if the results are statistically significant
    • Inferential statistics involve hypothesis testing and p-values.

      True
    • A bar chart could display mean scores on a psychology survey
    • Examples of qualitative data include interview transcripts and observation notes.

      True
    • Steps in hypothesis testing in inferential statistics
      1️⃣ State the null hypothesis
      2️⃣ Calculate a test statistic
      3️⃣ Determine the p-value
      4️⃣ Compare the p-value to a threshold
      5️⃣ Decide if the results are statistically significant