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AP Stats Chapter 1 Review

AP Stats Chapter 1 Review. Q1: The midpoint of the data. Mode. Mean. Median. You chose the mean and that is the average of the data. The midpoint of the data is the median . . Go to Q2. You chose the mode and that is the observation with the highest frequency.

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AP Stats Chapter 1 Review

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  1. AP StatsChapter 1 Review

  2. Q1: The midpoint of the data Mode Mean Median

  3. You chose the mean and that is the average of the data. The midpoint of the data is the median. Go to Q2

  4. You chose the mode and that is the observation with the highest frequency. The midpoint of the data is the median. Go to Q2

  5. Correct! Way to go!! The midpoint of the data is the median. Go to Q2

  6. Q2: This graph is an example of: Symmetric Skewed right Skewed left

  7. You chose symmetric, the graph below is symmetric. This graph from Q2 is skewed right. Go to Q3

  8. You chose skewed left. This is an example of skewed left. Remember a graph is skewed in the direction of the tail. So the graph in Q2 would be skewed right. Go to Q3

  9. You’re right! A graph is skewed in the direction of the tail. So the graph in Q2 would be skewed right. Go to Q3

  10. Q3: Which one of these is NOT a measure center? Standard Deviation Mean Median

  11. You are right! Standard deviation is a measure of how spread out the data is. Mean and median are both measures of center. Go to Q4

  12. Mean and median are both measures of center. Standard deviation is a measure of how spread out the data is, not center. Go to Q4

  13. Q4: Males, Teenagers, Phone numbers are all examples of what type of data? Quantitative Critical Qualitative

  14. There is no such thing as critical data. Males, Teenagers, Phone numbers are all examples of qualitative or categorical data. Go to Q5

  15. Quantitative data is numerical data that would make sense to take the average or mean of it. Males, Teenagers, Phone numbers are all examples of qualitative or categorical data. Go to Q5

  16. You’re right! Males, Teenagers and Phone numbers are all examples of qualitative or categorical data. Quantitative data is numerical data that would make sense to take the average or mean of it. Go to Q5

  17. Q5: The best graphical representation for quantitative data is: Bar Graphs and Pie Charts Standard normal curve Histograms and Stemplots

  18. The best graphical representation for quantitative data is histograms, stemplots and dotplots. Bar graphs and pie charts are the best graphical representation for qualitative data. Go to Q6

  19. The best graphical representation for quantitative data is histograms, stemplots and dotplots. Bar graphs and pie charts are the best graphical representation for qualitative data. A standard normal curve is a representation for the distribution of symmetrical data. It does not give specific information that is needed for a graphical representation. Go to Q6

  20. You are right! But also remember that bar graphs and pie charts are the best graphical representation for qualitative data. Go to Q6

  21. Q6: Another word for Ogives is: Percentiles Cumulative Frequency Relative Frequency

  22. Another word forogivesis cumulative frequency. It means to adds up the frequency of the observations that fall at or below a specific observation. A percentile is the percentage of observations that fall at or below a specific observation. Go to Q7

  23. Another word forogivesis cumulative frequency. It means to adds up the frequency of the observations that fall at or below a specific observation. Relative frequency is how often an outcome is observed. Go to Q7

  24. You are right!! A percentile is the percentage of observations that fall at or below a specific observation. Relative frequency is how often an outcome is observed. Go to Q7

  25. Q7: The Interquartile Range (IQR) is: Q1- Q3 Q3- Q1 Q3- Q2

  26. No, sorry! The Interquartile Range (IQR) is Q3-Q1 Go to Q8

  27. You are right!! The Interquartile Range (IQR) is Q3-Q1 Go to Q8

  28. Q8: To calculate if a observation is a lower outlier, you would do the following: Q1-1.5(IQR) Q1 +1.5(IQR) 1.5Q1-IQR

  29. If an observation is less than or smaller than Q1-1.5(IQR) that observation is an outlier. Go to Q9

  30. Good Job! You are right! If an observation is less than or smaller than Q1-1.5(IQR) that observation is an outlier. Go to Q9

  31. Q9: The 5 number summary is best to describe this type of data: Symmetric Normal Non-normal

  32. Mean and median work best for symmetrical data. The 5 number summary is best to describe non-normal or skewed data. Go to Q10

  33. Good Job! You are right! The 5 number summary is best to describe non-normal or skewed data. Mean and median work best for symmetrical data. Go to Q10

  34. Q10: This tells us what values the variable takes and how often it takes these values. Correlation Distribution Variance

  35. No, sorry. Correlation tells us the strength of the relationship between 2 variables. The distribution tells us what values the variable takes and how often it takes these values. (Variance is the standard deviation squared.) End!

  36. No, sorry. Variance is the standard deviation squared. The distribution tells us what values the variable takes and how often it takes these values. (Correlation tells us the strength of the relationship between 2 variables.) End!

  37. You are right, distribution does tell us what values the variable takes and how often it takes these values. Correlation tells us the strength of the relationship between 2 variables. Variance is the standard deviation squared. End!

  38. Thanks for reviewing the Chapter 1 vocabulary!

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