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OCR GCSE Psychology
Unit 7: Research Methods
7.4 Data Analysis
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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
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