1. Statistical Reasoning in Everyday Life
Module 7
Statistical Reasoning in Everyday Life

2. 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…

3. 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.

4. 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

5. 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.

6. 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

7. 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