Mr. Rogers - AP Statistics Objectives
Syllabus 1st Quarter 2nd Quarter 3rd Quarter 4th Quarter
11 t-Test 12 Inf for Prop 13 Chi Test 14 Regession HT  
Unit Plan Practice Test
Latin

Latin/Greek Root Words

arch--------->ancient, example: archtype;         chrono------>time, example: chronology;             -dom----------->quantity/state, example: freedom               fer-------->carry, example: transfer;               gen--------->birth, example: generate;                 luc-------->light, example lucid;                 neo--------->new, example: neonatologist;                olig--------->few, example: oligarchy;              omni--------->all, omniscient;            sym--------->together, symbol;

(Statistics connection)

AP Statistics Standards

IV. Statistical Inference: Confirming models

A. Confidence intervals

IV. Statistical Inference: Confirming models (continued)

B. Tests of significance

C. Special case of normally distributed data

  1.  t-distribution
  2. Single sample t procedures
  3. Two sample (independent and matched pairs) t procedures

 

Objectives

Essential Question: How can we account for the greater uncertainty of analyzing data when sample size is small and little is known about the population?

Ch 11

  1. State the 2 assumptions for drawing inferences about a population mean when sigma is not known.

  • SRS

  • Normal Distribution of the population (symmetrical with single peak)

  1. Calculate standard error of a statistic (standard deviation of the sampling distr. = s/(n^.5) .

  2. Explain when a t statistic is used rather than a z score.

  3. Calculate t statistics.

  4. State the degrees of freedom for a t test. df = (n-1)

  5. Construct confidence intervals using the t statistic.

ME = t* s/(n0.5)

  1. Perform one sample t-procedures:

  • by hand (using the calculator only for basic mathematics) using t-tables.

  • by hand, using the calculator only for basic mathematics and finding areas

  • using the hypothesis testing features of the TI-83

  • using Minitab software

 

Homefun: 11.7, 11.9,  -- Read section 

 

Activities

Lesson 1
Key Concept:  How is t-Distribution used?

Warm up: What conditions must be met to use a z-test?

Interactive Discussion: Objectives. What conditions must be met to use a t-test and how does this differ from a z-test?

Assuming a t-test is called for, what kinds of tests should be performed before using a t-test?

 

 

Essential Question: What is the single most powerful form of hypothesis testing and why ?

Matched Pairs Testing (Spanish Camp)

  1. Apply the t-test of significance to matched pairs situations. (1 sample t-test, Ho = 0, df = (number of pairs - 1), be aware: you must establish that the population is approximately normally distributed.)

How to Establish That a Population is Normally Distributed

Box Plot - symmetrical, box width smaller than a whisker's width

Normal Quantile Plot - straight line

  1. Explain what is meant by a robust test or confidence interval. (p-value  or confidence interval changes little if assumptions violated.)

  2. Be as one with the information in the "using t procedures" box on p.636.

  3. Be aware that outliers are very harmful to the t-test.

 

Homefun:  11.13, 11.17, 11.21, 11.26 

 

Lesson 2
Key Concept: How are Matched Pairs t-test used.

Warm up questions (individuals):

  1. What two assumptions must be met to use a t-test?
  2. How do you know you have normally distributed data?
  3. What step must you take before using a t-test of any kind?

Interactive Discussion: Set up confidence intervals and hypothesis tests for matched pairs.

Problem Solving (Teams of two): Make a hypothesis test with matched pairs for a pre and post test situation--Spanish Camp

 

Essential Question: How can you determine if 2 populations differ if at the start you have no information?

Ch 11

  1. State the assumptions made for two-sample tests. (p. 650)

  • Samples from an SRS

  • normally distributed

  • independent - matching violates independence

  1. Create confidence intervals and hypothesis test using two sample t procedures assuming that the sigmas of the two populations are unequal. This is the most conservative assumption.

Test Statistic for  Hypothesis Testing Margin of Error for Confidence Interval
t = (xbar1 -xbar2) - 0
(s12/n1 + s22/n2)0.5
ME = t* (s12/n1 + s22/n2) 0.5
  1. Create confidence intervals and hypothesis test using two sample t procedures and the most conservative method of determining df. (the lower of n1 -1 or n2 - 1)

  2. Be aware of the more accurate way to calculate df as shown on page 659.

  3. Perform two sample hypothesis t-procedures on the TI-83.

  4. State the key assumption required for using the pooled two-sample t-procedures.

  • The sigmas of the two populations are the same

Homefun 11.33, 11.35, 11.37, 11.49: 

Lesson 3
Essential Question:  How are two sample t-procedures -- no assumption made about the standard deviation being equal(p.624)--used?
 
 
Warm up questions (Individual):
  1. What two types of tools are used for inference?
  2. What type of distribution is used for making inferences?

Interactive Discussion: Set up a hypothesis test for two samples and point out how it differs from Z-test

 
Problem Solving (Teams of two): Make a hypothesis test with 2 sample and matched pairs for a pre and post test situation--return to the Spanish Camp data.

 

 

 

 

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