ap stats study guides

โœŒ๏ธย  Unit 2 - Exploring Two-Variable Data

โš–๏ธย  Unit 6 - Inference for Categorical Data: Proportions

๐Ÿ˜ผย  Unit 7 - Inference for Qualitative Data: Means

โœณ๏ธย  Unit 8 Inference for Categorical Data: Chi-Square

๐Ÿ“ˆย  Unit 9 - Inference for Quantitative Data: Slopes

๐Ÿงย  Multiple Choice Questions (MCQs)

7.0 Unit 7 Overview: Inference for Quantitative Data: Means

#quantitativedata

#confidenceintervals

#populationmean

#significance

โฑ๏ธย ย 1 min read

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October 28, 2020

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Have you ever been given a piece of information and said "๐Ÿค”๐Ÿค” That just doesn't sound right!" In this unit, we are going to tackle how we can actually test these claims when dealing with quantitative data.

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Confidence Intervals

Half of this unit is dedicated to constructing and interpreting confidence intervals. A confidence interval is a range of numbers with which we can estimate a true population mean/proportion.

We can take a sample drawn randomly from our population and calculate an interval that can be reflective of the true population mean to a certain confidence level.

Significance Tests

The other half of this unit is dedicated to significance tests. This is when we have a claim from the author regarding the true population mean, but we also have a sample mean and standard deviation that leads us to doubt this claim.

For example, the local Co-Op says that they get in approximately 25 ๐Ÿค every Thursday. You have been checking their inventory for 35 days and have found the average number of ๐Ÿค to be only 21. Is the Co-Op not being truthful or are your different findings due to simply sampling variability? Read on to determine how to test their claim...

๐ŸŽฅWatch: AP Stats - Inference: Confidence Intervals for Means

๐ŸŽฅWatch: AP Stats - Inference: Hypothesis Tests for Means

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