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Psychological Research Data Analysis

Quantitative vs Qualitative Definitions

Understanding the difference between these types is crucial for selecting appropriate methods of data collection and analysis.

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Quantitative Data

Numerical information that can be measured and expressed using numbers. This type of data is objective.
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Qualitative Data

Descriptive and non-numerical. Captures qualities, meanings, and subjective experiences (e.g., from interviews).

Data Collection Distinction

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Quantitative Techniques Use structured methods such as controlled experiments, standardized surveys. The focus is on reliability and objectivity.
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Qualitative Techniques Involve less structured methods: semi-structured interviews, participant observation. This approach is more subjective.

Primary vs Secondary Data

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Primary Data (Advantages) Data collected firsthand by the researcher specifically for the purposes of their study. It is tailored to the research question.
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Secondary Data (Disadvantages) Data that already exists, collected by someone else. Researcher has no control over how it was collected and may encounter issues with accuracy or relevance.

Meta-Analysis and Statistical Power

Definition and Purpose

Meta-analysis is a form of secondary data analysis involving statistically combining results from multiple primary studies on the same topic to produce an overall conclusion. It provides an objective summary and increases statistical power.

Descriptive Statistics: Summary Measures

Descriptive statistics summarize and organize data to describe the main features of a dataset.

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Central Tendency

Identify a typical or central value (Mean, Median, Mode).
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Measures of Dispersion

Indicate how spread out the data are, showing variability or consistency (Range, Standard deviation).

The Mean Calculation

Mean: sum all scores ÷ number of scores
The arithmetic average. It is sensitive to extreme values (outliers), which can skew the result.

Types of Correlation

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Positive correlation: Both variables increase together (e.g., study time and test scores).
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Negative correlation: One variable increases as the other decreases (e.g., hours of exercise and body fat).
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Zero correlation: No relationship between the variables.

Pro Tip: Understanding Dispersion

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Standard Deviation (SD): SD is the most informative measure of dispersion as it measures the average variability around the mean.

Visual Data Presentation

Different graph types serve various purposes depending on the data type and relationships being shown.

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Scattergrams

Display paired data points for two continuous variables. Useful for visualizing correlation.
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Bar Charts

Show comparisons between discrete categories or groups (nominal or ordinal data).
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Histograms

Used for continuous data that are divided into intervals (bins). Bars are adjacent.

Skewed Distributions

Normal Distribution Baseline: Symmetrical and bell-shaped, with Mean = Median = Mode. Many statistical tests assume this shape.

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Positive Skew (Right) Tail extends to the right; mean > median > mode. Data clusters on the left side.
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Negative Skew (Left) Tail extends to the left; mean < median < mode. Data clusters on the right side.

Interpreting Correlation

Direction and Strength

Correlation measures the strength and direction of a relationship between two variables. Coefficients range from -1 to +1. Pearson’s r is used for interval or ratio data that are normally distributed and linearly related.

Correlation Coefficient Magnitude

The magnitude (absolute value) indicates the strength of the linear association.

Range Strength Range Strength
0.0 to ±0.1 very weak ±0.5 to ±0.7 strong
±0.1 to ±0.3 weak ±0.7 to ±1.0 very strong
±0.3 to ±0.5 moderate

Levels of Measurement

The level describes the nature of the data and affects which statistical analyses are appropriate.

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Nominal Level

Data are categories with no inherent order. Comparisons mean equality/inequality only (e.g., gender).
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Ordinal Level

Data have a meaningful order or rank, but intervals between ranks are not equal (e.g., class rankings).
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Interval Level

Numerical data with equal intervals between values but no true zero point (e.g., temperature in Celsius).

Coding in Content Analysis

Coding involves categorizing data into units that represent meaningful concepts, transforming qualitative data for systematic analysis.

1

Develop Coding Scheme

Create categories derived from the research question or theory.
2

Assign Segments

Read the data and assign segments to appropriate codes (Manifest or Latent content).
3

Ensure Reliability

Verification through clear definitions and multiple coders (inter-rater reliability).
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Quantitative and Qualitative Data Deck
Term
Quantitative Data

What is quantitative data?

Answer
Definition

Numerical information that can be measured and statistically analyzed.

Term
Examples of Quantitative Data

Give examples of quantitative data.

Answer
Examples

Reaction times, IQ scores, height, number of correct answers.

Term
Qualitative Data

What is qualitative data?

Answer
Definition

Descriptive, non-numerical information capturing meanings and experiences.

Term
Qualitative Data Collection Methods

Name common qualitative data collection methods.

Answer
Methods

Interviews, open-ended questionnaires, observations, content analysis.

Term
Primary Data

What distinguishes primary data?

Answer
Definition

Data collected firsthand by the researcher for their specific study.

Term
Secondary Data

What is secondary data?

Answer
Definition

Data originally collected by others for different purposes.

Term
Meta-Analysis

Define meta-analysis.

Answer
Definition

Statistical combination of results from multiple primary studies.

Term
Measures of Central Tendency

What are measures of central tendency?

Answer
Definition

Mean, median, and mode.

Term
Calculating the Mean

How is the mean calculated?

Answer
Definition

Sum of all scores divided by the number of scores.

Term
Standard Deviation

What does standard deviation measure?

Answer
Definition

The average amount of variability or spread around the mean.

Term
Graph for Paired Quantitative Data

What type of graph shows paired quantitative data points?

Answer
Graph Type

Scattergram (scatterplot).

Term
Normal Distribution

Describe a normal distribution.

Answer
Description

Symmetrical, bell-shaped distribution where mean = median = mode.

Term
Positive Correlation

What does a positive correlation indicate?

Answer
Meaning

Both variables increase together.

Term
Levels of Measurement

Name the three levels of measurement.

Answer
Levels

Nominal, ordinal, and interval.

Term
Coding in Content Analysis

What is coding in content analysis?

Answer
Definition

Categorizing qualitative data into units for analysis.

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📊 Quantitative and Qualitative Data Quiz

1. Which of the following is an example of qualitative data?

Qualitative data is descriptive and non-numerical, like descriptions of feelings.

2. Which measure of central tendency is least affected by outliers?

Median is the middle value and is less sensitive to extreme scores.

3. Meta-analysis combines data collected firsthand for a specific study. (True or False)

Meta-analysis uses secondary data from multiple primary studies.

4. Which visualization is best for illustrating a correlation between two continuous variables?

Scattergrams display paired quantitative data to show correlations.

5. What does a positive correlation indicate between two variables? (Short Answer)

Both variables increase together.

6. Nominal data refers to:

Nominal data is categorical without ranking.

📊 Results

  • Notes and Quiz
  • Psychology
  • AS & A Level
  • Social Psychology
  • AQA