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Creating Run Charts
It’s important for our data to be the result of random sampling because if not, it will lead to inaccurate results and conclusions. The Run Chart allows us to test our data set for randomness and independence before conducting more advanced statistical analysis. Learn the components of a run chart and the tests we can run to check for randomness of our data.
Course Videos
Inferential Statistics Overview and Sampling
05:25
2Hypothesis Testing Overview
07:49
3Normality
07:36
4Central Limit Theorem
07:25
5The Z-Score
07:40
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Creating Run Charts
04:56
Next Video1-Sample t-Test
06:34
82 Variances Test
08:58
92 Sample t-Test
07:53
10Paired t-Test
06:30
111-Proportion Test
04:49
122 Proportions Test
06:46
13Chi Square Test
11:09
141 Sample Sign Test
03:59
15Mann-Whitney Test
04:48
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Next Video 1‑Sample t‑Test
A 1‑Sample t‑Test is a statistical hypothesis test that we use to make inferences about a population mean based on data from a random sample. It’s effective even for small sample sizes. Learn the assumptions and the steps for conducting a 1‑sample t‑test.