Scatter Plots, Lines of Best Fit and TI-84 Tips
Our district pacing allows only for two days to a lot of information around scatter plots - correlation coefficient as a measure of the strength of the linear association, and writing linear...
Handling Statistical Hypothesis Tests - dummies
You use hypothesis tests to challenge whether some claim about a population is true (for example, a claim that 40 percent of Americans own a cellphone). To test a statistical hypothesis, you take a sample, collect data, form a statistic, standardize it to form a test statistic (so it can be interpreted on a standard […]
Summarizing Statistics (Bell Curve Distribution) Poster
Your walls are a reflection of your personality, so let them speak with your favorite quotes, art, or designs printed on our custom posters! Choose from up to 5 unique, high quality paper types to meet your creative or business needs. All are great options that feature a smooth, acid-free surface with vibrant full color printing. Browse through standard or custom size posters and framing options to create art that’s a perfect representation of you. Ideal for vibrant artwork and photo…
Z-statistics vs. T-statistics | Inferential statistics | Probability and Statistics | Khan Academy
Z-statistics vs. T-statisticsWatch the next lesson: https://www.khanacademy.org/math/probability/statistics-inferential/hypothesis-testing/v/small-sample-hyp...
How to find Z Scores and use Z Tables? (9 Amazing Examples!)
Learn how to calculate a z score, create a standard normal distribution curve, and use a z table to determine the probability of an event occurring. Discover the difference between the standard deviation and z-score as well as how the empirical rule compares with z score tables.
How to find the Line of Best Fit? (7+ Helpful Examples!)
Learn how to determine the correlation for various scatter plots and determine whether the relationship is linear or nonlinear. Then discover the steps for creating best-fit lines for various sample data and predict future values using linear approximation.