Data Analysis Guide, Qualitative vs Quantitative Data, Research Methods in Psychology, Introduction to Discourse Analysis, Thematic Analysis Techniques, Understanding Content Analysis, Discrete vs Continuous Data, Primary and Secondary Data Sources, Meta-Analysis Explained, Levels of Measurement in Research, Descriptive Statistics Overview, Raw Data Processing, Qualitative Data Collection, Advantages of Qualitative Research, Challenges in Qualitative Data Analysis, Quantitative Research Methods, Physiotherapy and Stroke Recovery Studies Rebecca Sylvia Data Analysis Guide, Qualitative vs Quantitative Data, Research Methods in Psychology, Introduction to Discourse Analysis, Thematic Analysis Techniques, Understanding Content Analysis, Discrete vs Continuous Data, Primary and Secondary Data Sources, Meta-Analysis Explained, Levels of Measurement in Research, Descriptive Statistics Overview, Raw Data Processing, Qualitative Data Collection, Advantages of Qualitative Research, Challenges in Qualitative Data Analysis, Quantitative Research Methods, Physiotherapy and Stroke Recovery Studies Rebecca Sylvia

DATA HANDLING AND ANALYSIS

"Data Handling and Analysis: From Descriptive Statistics to Meta-Analysis"

Explore the basics of data handling and analysis in psychology, including descriptive statistics, measures of central tendency (mean, median, mode), measures of dispersion (range, variance, standard deviation), and the differences between qualitative and quantitative data. Learn how psychologists use meta-analysis to combine and interpret findings across multiple studies. Perfect for students seeking to strengthen their grasp of psychological research methods.

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Data Analysis Guide, Meta-Analysis Explained, Raw Data Processing Rebecca Sylvia Data Analysis Guide, Meta-Analysis Explained, Raw Data Processing Rebecca Sylvia

DISCREET AND CONTINUOUS DATA

CONTINUOUS AND CATEGORICAL DATA

Data in psychology can be categorised as continuous or categorical (also called discrete). Continuous data refers to numerical values that can take any value within a range, such as height, weight, or reaction time. It is measured on a scale and often analysed using means or standard deviations.

Categorical data, on the other hand, involves distinct categories or groups. Examples include gender, ethnicity, or types of therapy. This data is non-numerical and is often summarised using frequencies or percentages.

Understanding the distinction is key to choosing the right statistical tests and interpreting psychological research effectively.

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