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Simple Linier Regression
Simple Linear Regression Department of Statistics, ITS Surabaya Slide- Prepared by: Sutikno Department of Statistics Faculty of Mathematics and Natural Scienc…
How to Calculate Confidence Interval: 6 Steps (with Pictures)
A confidence interval is an indicator of your measurement's precision. It is also an indicator of how stable your estimate is, which is the measure of how close your measurement will be to the original estimate if you repeat your...
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
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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...
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.