Questions to answer for Section 8-3 can be found here.
Practice worksheet for Proportion and Mean Confidence Intervals can be found here.
Answers to practice are here. Question 1. Question 2
Thoughts and Questions on 9-1 are here.
Thoughts on Section 9-3 are here.
Another practice FRQ is here. (do question 6)
Chapters 8, 9 and 10 Test on Confidence Intervals and Hypothesis Testing is available
The multiple choice is here. The free response is here.
Submit by Thursday, April 23rd.
The multiple choice is here. The free response is here.
Submit by Thursday, April 23rd.
Past AP Stats Practice Exams
You can find all past practice FRQ's here.
I looked through the exams from 2018 back to the 2010 Form B exam and found the following questions that you should not do (they ask for material not covered this year)
2017 #5
2016 #2, 6 part a
2014 #1 part c
2013 #4
2011 #5 part d
2011 Form B #4
2010 #6 parts d, e
2010 Form B #5 part d, 6 part d
The frq's cover all the general topics we covered in the class and will be good practice for the exam. Also, the answers are available on the same website as the exam questions so you can check your work.
Exam is May 22nd!
I looked through the exams from 2018 back to the 2010 Form B exam and found the following questions that you should not do (they ask for material not covered this year)
2017 #5
2016 #2, 6 part a
2014 #1 part c
2013 #4
2011 #5 part d
2011 Form B #4
2010 #6 parts d, e
2010 Form B #5 part d, 6 part d
The frq's cover all the general topics we covered in the class and will be good practice for the exam. Also, the answers are available on the same website as the exam questions so you can check your work.
Exam is May 22nd!
May 18th: Chs 1, 2, 4 reminders
Two types of data - categorical and quantitative
Pictures for data: Categorical - bar chart or pie graph
Quantitative - dot plot, stem and leaf, box and whisker, histogram
Measures of center: mean (if data is symmetrical), median (if data is skewed)
Measures of spread: st. dev (if data is symmetrical), IQR (if data is skewed), range (for either)
Describing distributions of data: Remember SOCS: shape, outliers, center, spread
Differences between and observation vs experiment
Stratification and blocking mean the same thing - stratification for gathering data, blocking for experimentation
Know how to randomly assign people into an experiment
Two types of data - categorical and quantitative
Pictures for data: Categorical - bar chart or pie graph
Quantitative - dot plot, stem and leaf, box and whisker, histogram
Measures of center: mean (if data is symmetrical), median (if data is skewed)
Measures of spread: st. dev (if data is symmetrical), IQR (if data is skewed), range (for either)
Describing distributions of data: Remember SOCS: shape, outliers, center, spread
Differences between and observation vs experiment
Stratification and blocking mean the same thing - stratification for gathering data, blocking for experimentation
Know how to randomly assign people into an experiment
May 19th Ch 5, 6 Reminders
Probability = (outcomes you want)/(total number of outcomes)
Probability Model shows all possible outcomes and has a total probability of 1
Addition Rule: P(A or B) = P(A) + P(B) - P(A and B)
Multiplication Rule: P(A and B) = P(A) * P(B|A)
Know difference between mutually exclusive and independence
mutually exclusive: P(A and B) = 0
independent: P(B|A) = P(B)
Conditional Probability: P(A|B) = P(A and B)/P(B) - multiplication rule rewritten
Be able to organize data with tables, Venn diagrams, tree diagrams.
Don't forget first rule of probability
Random Variables - discrete vs continuous
Combining Random Variables - what affects the mean, what affects the standard deviation, remember to use variance
Binomial Distribution - remember BINS
Geometric Distribution - special case of binomial with only one success at the end
Know how to find and use on calculator
Probability = (outcomes you want)/(total number of outcomes)
Probability Model shows all possible outcomes and has a total probability of 1
Addition Rule: P(A or B) = P(A) + P(B) - P(A and B)
Multiplication Rule: P(A and B) = P(A) * P(B|A)
Know difference between mutually exclusive and independence
mutually exclusive: P(A and B) = 0
independent: P(B|A) = P(B)
Conditional Probability: P(A|B) = P(A and B)/P(B) - multiplication rule rewritten
Be able to organize data with tables, Venn diagrams, tree diagrams.
Don't forget first rule of probability
Random Variables - discrete vs continuous
Combining Random Variables - what affects the mean, what affects the standard deviation, remember to use variance
Binomial Distribution - remember BINS
Geometric Distribution - special case of binomial with only one success at the end
Know how to find and use on calculator
May 21st Chs 7, 8, 9, 10, 3 Review
Sampling Distribution has an unbiased measure of center and a biased measure of spread
Conditions: 10% Rule for Independence and Large Counts for approximate normality
For means, Large Counts is Central Limit Theorem
Links for confidence intervals and hypothesis testing types (didn't do chi-square test) are here and here.
Go back over Ch 3 and linear regression. What does r say about the data? What does r-sq say about the data? What are residuals and what is a residual plot used for?
Sampling Distribution has an unbiased measure of center and a biased measure of spread
Conditions: 10% Rule for Independence and Large Counts for approximate normality
For means, Large Counts is Central Limit Theorem
Links for confidence intervals and hypothesis testing types (didn't do chi-square test) are here and here.
Go back over Ch 3 and linear regression. What does r say about the data? What does r-sq say about the data? What are residuals and what is a residual plot used for?