Guyer High School
Where Tradition Begins and Excellence Continues
 Guyer High School
 AP Statistics
 Calendar of Lessons & Assignments
Matamoros, Bridget  Math

Lesson Material and Schedule Outline
The below information is also posted on Canvas and can be accessed through the SSO (sso.dentonisd.org) or dentonisd.instructure.com using the google student sign in information for those who have received and accepted a Canvas invitation through email.MODULE/UNIT 1Unit 1 Objectives: (Lesson number is in parenthesis)
Data in general:
 Identify and classify variables as Categorical (binary) or Quantitative (discrete or continuous) (1.2)
 Collect data measured with various categorical and quantitative variables using frequency tables (1.2, 1.3)
Categorical Data:
 Determine the marginal distribution of a categorical variable (1.2)
 Calculate relative frequencies and conditional frequencies from a distribution of categorical data (1.2)
 Represent categorical data using bar charts, segmented bar charts, and pie charts (1.2)
 Describe and interpret a distribution of categorical data from various representations (1.2)
Quantitative Data:
 Represent quantitative data using box plots, histograms, and stemandleaf plots (1.3, 1.4)
 Describe and interpret a distribution of quantitative data using measures of center, unusual qualities, shape, and spread (1.3, 1.4, 1.5)
 Compare two distributions of quantitative data (1.4)
 Calculate the 5number summary of a data set (1.3)
 Calculate the fence value for a box plot and determine if outliers exist (1.3)
 Describe and/or calculate the effects of outliers on the 5number summary, mean, median, range, IQR, standard deviation, and variance of a data set (1.5)
 Describe and/or calculate the effects of adding or removing a data point on the five number summary (1.5)
 Know the difference between robust and nonrobust statistics (1.5)
Schedule:
First Day August 16/17Overview of Statistics: Smelling Parkinson's Investigation/SimulationQuick Syllabus Review, answer any questionsHW: Complete Module 0 in CanvasLesson 1.2: Types of Data; Collecting and Representing Categorical DataDates: August 18 (A) and 21 (B)Lesson Notes Overview: https://www.smore.com/t844tapstatisticsGraphing Data: https://onlinecourses.science.psu.edu/stat500/node/113Contingency Tables (Pearson Video): http://mediaplayer.pearsoncmg.com/assets/_embed.true/NAcppI5cLh5i2M90WkstKhki8R2q0E8vHomework: Pages 3839 #23, 24, 25, 26Lesson 1.3A: Representing and Summarizing Quantitative Data with Histograms and StemandLeaf PlotsDates: August 22 (A) and 23 (B)Graphing Data: https://onlinecourses.science.psu.edu/stat500/node/113Summarizing Data (PSU Online Lessons 2.1 through 2.3): https://onlinecourses.science.psu.edu/stat500/node/11Summarizing a Distribution (Pearson Videos): http://mediaplayer.pearsoncmg.com/assets/_embed.true/7Sauwc2Q3GsNfXr_Izjt91kHKTN5VflNHomework: Pages 7379 #5, 9, 44, 45, 48Lesson 1.3B: Representing and Summarizing Quantitative Data with Numerical Measures and Box PlotsDates: August 24 (A) and 25 (B)(Powerpoint Notes for Chapter 3 in lesson 1.3A)Graphing Data: https://onlinecourses.science.psu.edu/stat500/node/113Summarizing Data (PSU Online Lessons 2.1 through 2.3): https://onlinecourses.science.psu.edu/stat500/node/11Boxplots and Outliers (Pearson Videos): http://mediaplayer.pearsoncmg.com/assets/_embed.true/5lod3safhChLl5h1BKPwyS5pMnotSVURStandard deviation: http://mediaplayer.pearsoncmg.com/assets/_embed.true/2i8uwvL34Lq8aHcSk8lgyPfplPDape_fHomework: Pages 7578 #18, 19, 28, 33, 37Lesson 1.4: Comparing Two or More Distributions of Quantitative DataDates: August 28 (A) and 29 (B)Graphing Data: https://onlinecourses.science.psu.edu/stat500/node/113Summarizing Data (PSU Online Lessons 2.1 through 2.3): https://onlinecourses.science.psu.edu/stat500/node/11Comparing Distributions (Pearson Videos): http://mediaplayer.pearsoncmg.com/assets/_embed.true/O0gFlAxDttf41j1Lw6P7093pF_BPNbelHomework: Pages 97101 #7, 12, 15, 23, 26Lesson 1.5: Determining Effects of Changing Data on Summary MeasuresDates: August 30 (A) and 31 (B)Summarizing Data (PSU Online Lessons 2.1 through 2.3): https://onlinecourses.science.psu.edu/stat500/node/11Homework: Pages 131133 #5, 11, 12, 24Review for Unit 1 Test and catchupDates: September 1 (A) and 5 (B)Test Review: Pages 138146 #1, 11, 15, 16, 18, 19, 28, 31 (omit f), 32 (omit d & e), 33Unit 1 Test: Categorical and Quantitative DataDates: September 6 (A) and 7 (B)AP Set #1 Due on test dayHW: Take the free online IQ test and print out your results OR take a screen shot to show me in class. http://www.freeiqtest.net/MODULE/UNIT 2Note: Lessons 2.11A and 2.11B are switched on purpose.
Lesson 2.11B: Recognizing Sources of BiasActivity and Goal: Students will use examples of bias to create a skit representing a given type of bias; Students will compare/contrast the various types of bias presentedDates: September 8 (A) and 11 (B)Homework: Pages 301 #12, 13, 15, 16Lesson 2.11A: Types of Sampling MethodsActivity and Goal: Students will use and compare various sampling methods and discover their effects on estimating a population parameterDates: September 12 (A) and 13 (B)Homework: Read pages 280  285 until the "Just Checking" box and complete the "Just Checking" exercise. Complete #7, 9, 10 on page 300301.Lesson 2.11C: Survey DesignActivity and Goal: Students will use their knowledge of bias and additional examples of political polls to design a survey for Guyer students assessing a topic determined by the class.Dates: September 14 (A) and 15 (B)Homework: Pages 302 #24, 25, 26Lesson 2.11D: Sampling from a populationActivity and Goal: Students will work with a partner to gather a sample of Guyer students from the sampling frame for implementation.Remaining time will be spent reviewing for the test next classDates: September 18 (A) and 19 (B)Homework: Pages 303304 #36, 37, 38; Finish AP Set #2Test Unit 2: Sample Surveys, Bias, & Sampling MethodsDates: September 20 (A) and 21 (B)AP Set #2 Due on test dayIQ PROJECTMain Objectives: Use graphical and numerical summaries to compare distributions of quantitative data; Use the empirical rule to calculate percentiles; Use a simulation to determine the existence of a statistically significant difference between two independent samplesDates: October 2/3 through 6/9DUE October 10 at the end of the day, no exceptions!MODULE/UNIT 3Unit 3 Objectives (Lesson number is in parenthesis)
The Normal Probability Distribution:
 Determine standardized values (zscores) for observations from various populations (3.5A)
 Use standardized scores to compare across different populations (3.5A)
 Use the Empirical Rule for efficient and accurate percentile calculations (3.5A)
 Use the Empirical Rule to efficiently determine observed values from given percentile rankings (3.5A)
 Use zscores to calculate onesided normal distribution probabilities with and without technology (3.5B)
 Use zscores to calculate twosided normal distribution probabilities with and without technology (3.5B)
 Use percentile rankings to determine specific observations from populations with and without technology (3.5C)
 Interpret ogive curves to determine the shape of a distribution and percentile rankings for observations (3.5C)
 Use systems of equations to solve for parameter values of nonstandard normal distributions (3.5C)
Schedule:Lesson 3.5A: Understanding the Normal Distribution
Dates: October 17, 19 (B) and 18, 20 (A)
Focus Topics: Comparisons with zscores, The Empirical Rule
Continuous Distributions (Focus on the Normal Distribution): https://onlinecourses.science.psu.edu/stat500/node/23
Link to smore notes: https://www.smore.com/4tqx8apstatistics
Homework 3.5A1: Pages 132135 #25, 26, 30, 35 Solutions
Homework 3.5A2: Pages 132133 #16, 17, 19, 22, 27 Solutions
Lesson 3.5B: Probability Calculations with the Normal Distribution
Dates: October 23, 25 (B) and 24, 26 (A)
Focus Topics: Using the normalcdf and invnorm functions in the calculator for one and twosided calculations
Solutions to Practice problems from the notes
Continuous Distributions (Focus on the Normal Distribution): https://onlinecourses.science.psu.edu/stat500/node/23
Homework 3.5B1: Page 136 #39, 40, 41, 42, 43 Solutions
Homework 3.5B2: Pages 136137 #46, 47, 48, 49 Solutions
Lesson 3.5C: Ogive Curves and Review
Dates: October 27 (B) and 30 (A)
Focus Topics: Creating and Reading Ogive curves; Review for Test
Homework 3.5C: Page 102 #29, 30; Test Review Solutions to handout
Normal Curve Practice Solutions (Handout we used as notes and highlighted colors of problems)
Test review problems from the textbook: SOLUTIONS
Unit 3 Test: The Normal Probability Distribution
Dates: October 31 (B) and November 1 (A)
AP Set #3 Due on test day
MODULE/UNIT 4Objectives for Regression and Correlation
 Calculate by hand and understand the theory behind the correlation coefficient (r)  why are the zscores of x and y used?
 Describe an association between two quantitative variables using strength (weak, moderate, strong), direction (positive, negative), and form (linear, nonlinear)
 Understand that a correlation between two variables does not imply that one causes the other
 Calculate by hand and understand the theory behind the Least Squares Regression Line
 Calculate and interpret the residuals from a regression model as well as the residual plot
 Determine if a particular residual corresponds to an overestimate or an underestimate of the response
 Interpret computer output from a regression analysis and use it to create a regression equation
 Interpret R2  "coefficient of determination"; the proportion of variation in the response that is explained by the predictor
 Interpret s  the standard deviation of the residuals; observations are on average s units from the LSRL
 Interpret t and p  is an explanatory variable a statistically significant predictor of the response?
 Interpret standard error of the slope
 Use CONTEXT when interpreting a regression equation, slope, and yintercept
 Use a regression equation to make a prediction about the response variable
 Use statistical software to perform a regression analysis on a bivariate data set
 Compare and contrast outliers and influential points
 Determine the effects of outliers and influential points on regression output
 Understand the dangers of extrapolation and identify when it is used in the media
Lesson 4.6: Correlation Does not imply Causation; Calculating and interpreting the Correlation CoefficientDates: October 20, November 1(B) and October 31, November 2 (A)
Spurious Correlations Activity: Nicholas Cage movies do not cause people to drown. (Or do they?)
Unpacking Past AP Exam Questions on Regression  what do you have to know about this unit?
Calculating the Correlation Coefficient with M&M's  It's all based on zscores
Key Words/Concepts: Explanatory Variable, Response Variable, Correlation Coefficient (r), Association, Strength and Direction of an Association
Video on association: https://mediaplayer.pearsoncmg.com/assets/_LDUYyhAE3mgU4ia6ejCl5zjI8_U6ODS
HW: Pages 167175 #2, 5, 9, 10, 47 SOLUTIONS
Lesson 4.7: What is the Least Squares Regression Line (LSRL)? How is it calculated and what do I have to interpret?
Dates: November 3, 7, 9 (B) and 4, 8, 10 (A)
Randomness and Scrabble Activity  Which variable explains the most about a word's Scrabble score? >Interpreting slope, yintercept, r, and Rsquared
Video Collection: Rsquared / Regression and LSRL / Slope and Yintercept
StepbyStep Calculating a Regression Equation
Homework 4.7A: Pages 199203 #2, 3, 11, 15, 16, 43abc SOLUTIONS
Due 11/7 (B) 11/8 (A)
Homework 4.7B: Finish Scrabble problem #3
Due 11/9 (B) 11/10 (A)
Homework 4.7C pg. 199205 #18, 38, 47, 49; Read pages 209221
Due 11/15 (B) 11/16 (A)
Barbie Bungie Jumping
Lesson 4.8/4.9
Dates: 11/15 (B) and 11/16 (A)
Linear Transformations with M&M's: How to determine a linear model when data are not linear
Backtransforming an equation to predict a yvalue
HW: Test Review (see below)
Review for Test
Pages 225229 #17, 19, 25, 31, 33
Pages 248253 #5, 7, 9, 1822
Pg. 264265 Multiple Choice #110
Unit 4 Test: Regression and Correlation
Dates: November 17 (B) and 18 (A)