review7 MAY 2014

Teddy Li

AP STATISTICS B

UNIT 5 CHAPTER 18-22• reject the null hypothesis• fail to reject the null hypothesis

• If Alpha is low and Power is low, more possibility for Type II Error

• SAMPLE MEANS: Quantitative Variable• SAMPLE PROPORTIONS: Categorical Variable

UNIT 5 CHAPTER 18-22, CONT.

• The power of a test concerns itself with the ability to detect an alternative hypothesis.

• When choosing a significance level alpha, you’re setting the probability of a Type I error to alpha.

• Z Test Statistic: • Always draw a picture!• Var(X-Y) = Var(X) + Var(Y)• SD2 = Var

UNIT 5 CHAPTER 18-22, CONT.• Parameter: true proportion of a population• Statistic: sample proportion• Central Limit Theorem: If the assumptions of SRS, 10% Condition,

Success/Fail and Independence are true, the data is approximately normal and you can use the normal model.

• Mean & SD for Sample Proportion: • Mean & SD for Sample Mean: • Mean:

UNIT 6 CHAPTER 23-25• Narrow confidence interval results from a larger sample size.• t test

• SRS, 10% Condition, Nearly Normal (Draw Histogram)

• Estimate Average number:

UNIT 6 CHAPTER 23-25, CONT.  Chapter 23: One Sample T (means) Chapter 24: Two Sample T (difference in means) Chapter 25: Paired T Test

Hypothesis write a statement 0 write a statement write a statement

Assumptions 1. SRS2. 10% Condition for mean3. Nearly Normal – check histogram

1. SRS2. 10% Condition for both means3. Independent Groups/Independence4. CLT (Central Limit Theorem)

1. SRS2. 10% Condition of sample3. Paired Data Assumption4. Nearly Normal – check histogram

Test an appropriate hypothesis

 

 

  

 

 

Reminder 

Conclusion 

At this alpha level, there [is/is not] enough evidence that the mean is equal to the null

At the alpha level, there [is/is not] enough evidence of a significant difference in [topic]

At this alpha level, there [is/is not] enough evidence that the before/after are the same

Sample Size Estimate

Use the same S and ME (given in problem)

none 

USE THE CALCULATOR TO FIND df

none 

USE THE CALCULATOR TO FIND df

Confidence Interval

UNIT 7 CHAPTER 26-27

• Goodness of Fit: determine how close the observed values fit the null; diff between observed and expected

• Homogeneity: compare distribution of counts for 2+ groups of SAME categorical variable; distributions are same

• Independence: test whether two DIFF categorical variables are independent; populations are independent

UNIT 7 CHAPTER 26-27, CONT.

• If you reject the null, RESIDUALS • Straight Enough Condition (scatterplot), Randomization Condition, Equal

Variance Condition (no pattern in residuals), Nearly Normal• Degrees of freedom: n-2

• CI

UNIT 7 CHAPTER 26-27, CONT.• Example

• T test: • 1.55 – 1.85

Variable Coeff SE(Coeff) t-ratio P-ValueIntercept -42.734 2.717 -15.7 <.0001Waist 1.70 .0743 22.9 <.0001