Statistical Reasoning in Everyday Life

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Statistical Reasoning in Everyday Life Module 7 Statistical Reasoning in Everyday Life

Descriptive statistics Descriptive statistics – numerical data used to measure and describe characteristics of groups Histogram – a bar graph depicting a frequency distribution Great display tool but can be easily manipulated Our brand of truck is better! Our brand of truck is not so different…

Descriptive statistics Measures of central tendency: Mode, Mean, Median Mean – most useful score and sensitive to extreme scores Skewed distribution – a representation of scores that lack symmetry around their average, most of scores are squeezed into one end.

Descriptive statistics Measures of variation: Range Standard Variation – computed measure of how much scores vary around the mean. Small standard deviation No animation. Large standard deviation Mean

Descriptive statistics Normal Curve – a symmetrical, bell-shaped curve that describes the distribution of many types of data; most scores fall near the mean (68% fall within one standard deviation) and fewer and fewer near the extremes.

Descriptive statistics Positive skew – when scores pull the mean toward the higher end of the scores Negative skew – when scores pull the mean toward the lower end of scores

Inferential Statistics Inferential statistics – numerical data that allow one to generalize – to infer from sample data the probability of something being true of a population Three principles to keep in mind when there is an observed difference between your experimental and control group – reliability: Must be a representative sample Low variability (small standard variation) – scores don’t vary much from the mean (not skewed) Large enough sample Statistical Significance – statistical statement of how likely it is that am obtained result occurred by chance When you have reliability (above criteria) Difference between mean of experimental and control group is large