✍️ Free Response Questions (FRQs)
👆 Unit 1 - Exploring One-Variable Data
1.4Representing a Categorical Variable with Graphs
1.5Representing a Quantitative Variable with Graphs
1.6Describing the Distribution of a Quantitative Variable
1.7Summary Statistics for a Quantitative Variable
1.8Graphical Representations of Summary Statistics
1.9Comparing Distributions of a Quantitative Variable
✌️ Unit 2 - Exploring Two-Variable Data
2.0 Unit 2 Overview: Exploring Two-Variable Data
2.1Introducing Statistics: Are Variables Related?
2.2Representing Two Categorical Variables
2.3Statistics for Two Categorical Variables
2.4Representing the Relationship Between Two Quantitative Variables
2.8Least Squares Regression
🔎 Unit 3 - Collecting Data
3.5Introduction to Experimental Design
🎲 Unit 4 - Probability, Random Variables, and Probability Distributions
4.1Introducing Statistics: Random and Non-Random Patterns?
4.7Introduction to Random Variables and Probability Distributions
4.8Mean and Standard Deviation of Random Variables
4.9Combining Random Variables
4.11Parameters for a Binomial Distribution
📊 Unit 5 - Sampling Distributions
5.0Unit 5 Overview: Sampling Distributions
5.1Introducing Statistics: Why Is My Sample Not Like Yours?
5.4Biased and Unbiased Point Estimates
5.6Sampling Distributions for Differences in Sample Proportions
⚖️ Unit 6 - Inference for Categorical Data: Proportions
6.0Unit 6 Overview: Inference for Categorical Data: Proportions
6.1Introducing Statistics: Why Be Normal?
6.2Constructing a Confidence Interval for a Population Proportion
6.3Justifying a Claim Based on a Confidence Interval for a Population Proportion
6.4Setting Up a Test for a Population Proportion
6.6Concluding a Test for a Population Proportion
6.7Potential Errors When Performing Tests
6.8Confidence Intervals for the Difference of Two Proportions
6.9Justifying a Claim Based on a Confidence Interval for a Difference of Population Proportions
6.10Setting Up a Test for the Difference of Two Population Proportions
😼 Unit 7 - Inference for Qualitative Data: Means
7.1Introducing Statistics: Should I Worry About Error?
7.2Constructing a Confidence Interval for a Population Mean
7.3Justifying a Claim About a Population Mean Based on a Confidence Interval
7.4Setting Up a Test for a Population Mean
7.5Carrying Out a Test for a Population Mean
7.6Confidence Intervals for the Difference of Two Means
7.7Justifying a Claim About the Difference of Two Means Based on a Confidence Interval
7.8Setting Up a Test for the Difference of Two Population Means
7.9Carrying Out a Test for the Difference of Two Population Means
✳️ Unit 8 Inference for Categorical Data: Chi-Square
📈 Unit 9 - Inference for Quantitative Data: Slopes
🧐 Multiple Choice Questions (MCQs)
Best Quizlet Decks for AP Statistics
⏱️ 2 min read
June 3, 2020
👨🏫We have discussed methods of sampling accurately but now, it is imperative to discuss how not to gather data. Statistical studies are biased if it is likely to underestimate or overestimate the value you are looking for.
Convenience Sampling chooses individuals from the population who are easiest to reach. This leads to underrepresented individuals from the resulting data. If you repeatedly conducted a convenience sample for the same population, your resulting average would either overestimate or underestimate the average for the population.
🙋♂️Voluntary Response Sampling allows people to choose whether they’d like to be included in the sample by responding to a general message. Often times, people who choose to participate feel strongly about the topic at hand and as a result, those who aren’t as interested or accounted for remain underrepresented.
Undercoverage happens when some members of the population are less likely to be chosen or can’t be chosen in a sample. For example, if you conduct a survey about the best communication methods by using Instagram, people who don’t have Instagram will not be included in the data.
🙅♂️Nonresponse is when an individual chosen for the sample can’t be reached or declines their participation. This actually leads to bias because the people who opt themselves out despite being chosen may have differing opinions that won’t be included in the results.
*Nonresponse occurs after a sample has been chosen while in a voluntary survey sample, every individual has chosen to take part so there wouldn’t be any nonresponse.
Response Bias occurs when there is a pattern of inaccurate answers to a survey. The way a question is worded impacts the response the person gives so identifying personal bias is important to ensure that the results are valid.
If sampling is done without considering the factors that could invalidate your results, then the concluding data and analysis will not be representative of the population.
Courtesy of Twitter
🎥Watch: AP Stats - Sampling Methods and Sources of Bias
2550 north lake drive
milwaukee, wi 53211
92% of Fiveable students earned a 3 or higher on their 2020 AP Exams.
*ap® and advanced placement® are registered trademarks of the college board, which was not involved in the production of, and does not endorse, this product.
© fiveable 2020 | all rights reserved.