2: What are Statistics?
- Page ID
- 49891
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- What does it mean when we say, “statistics uses comparisons?”
- Explain “estimation” in statistics.
Key Terms
- Descriptive statistics
- Inferential statistics
- Population parameter
- Sample statistic
Statistics is the study of variation. But what processes are involved when using statistics? The process of studying variation involves the following: organizing the variation and describing it, comparing the variation, looking for patterns in the variation, and making estimates, otherwise known as “guesses.”
We have already briefly examined how to organize variation and describe it. We determined what the “its” are, otherwise known as variables, and understood the variation by examining the “its” by type and by amount.
- 2.1: Statistics Involves Comparison and Context
- This page emphasizes the importance of context in understanding statistics and variations. It highlights how comparisons, particularly in the study of eating disorders among ethnic groups, reveal cultural influences on outcomes. Recognizing the significance of statistical context is vital for interpreting results accurately, whether distinguishing between actual effects and random variations or assessing treatment versus control groups.
- 2.2: Statistics is About Finding Patterns
- This page discusses data analysis, emphasizing the organization of numbers to uncover patterns that reveal systematic relationships between variables. It distinguishes between patterns and randomness, highlighting the role of statistics in identifying relationships—such as therapy effects on mental health. Statistical values are used to assess patterns against error variance, with higher values indicating stronger patterns, thereby aiding in decision-making during statistical tests.
- 2.3: Statistics as Estimates, or Making Guesses
- This page discusses the role of estimation in statistics as a means to make educated guesses about variables and patterns despite practical constraints. It highlights the distinction between population parameters (theoretical truths) and sample statistics (localized estimates). The emphasis is on using robust research design to improve the accuracy of these estimations, moving closer to universal truths.
- 2.4: Two Broad Categories of the Process of Using Statistics
- This page outlines the two main categories of statistics: descriptive and inferential. Descriptive statistics involves analyzing and summarizing data through frequency counts and measures of central tendency and variability. Inferential statistics follows, focusing on estimating relationships between variables using techniques such as t-tests, ANOVA, regression, and Chi-square analyses to extract insights from the data.