AP Stats Review. Assume that the probability that a baseball player will get a hit in any one at-bat is 0.250. Give an expression for the probability.

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Presentation transcript:

AP Stats Review

Assume that the probability that a baseball player will get a hit in any one at-bat is Give an expression for the probability that his first hit will next occur on his 5 th at bat? What kind of distribution is this?

A symmetric, mound-shaped distribution has a mean of 70 and a standard deviation of 10, find the 16 th percentile score.

Girls Boys

The table below give the estimated marginal cost for a piece of furniture. Find the residual amount for 400 units. Units Marginal Cost$300$250$220$200$180$175

What’s the difference between blocking & stratifying? Blocking is used in experiments while stratifying is used in surveys.

Find & interpret the correlation coefficient. Predictor Coef SE Coef T P Constant height S = R-Sq = 80.1% R-Sq(adj) = 76.8%

Name each type of sampling method: A. Code every member of a population and select 100 randomly chosen members. Simple Random Sample (SRS) B. Divide a population by gender and select 50 individuals randomly from each group. Stratified C. Select five homerooms at random from all of the homerooms in a large high school. Cluster D. Choose every 10 th person who enters the school. Systematic E. Choose the first 100 people who enters the school. Convenience

Find an estimate of the population slope if sample is size 10. (Use 95%) Predictor Coef SE Coef T P Constant height S = R-Sq = 80.1% R-Sq(adj) = 76.8%

If I increase the significance level, what happens to the power of the test? Explain. If I increase alpha, then Beta decreases. Thus the power of the test (1-Beta) will Increase.

The specifications fro the length of a part in a manufacturing process call for a mean of cm. Find the probability that a random sample of 50 of the parts will have a mean of cm or more if the standard deviation is 0.54.

Find & interpret the coefficient of determination. Predictor Coef SE Coef T P Constant height S = R-Sq = 80.1% R-Sq(adj) = 76.8%

Pre Post

A preliminary study has indicated that the standard deviation of a population is approximately 7.85 hours. Determine the smallest sample size needed to be within 2 hours of the population mean with 95% confidence.

Find & interpret the slope Predictor Coef SE Coef T P Constant height S = R-Sq = 80.1% R-Sq(adj) = 76.8% Slope = For every addition inch in height, the (y- variable) increases units.

What is the p-value? It is the probability that I got this sample, as extreme as it may be, if the Ho was really true.

Explain the power of a test. It is the probability that rejecting the Ho is the correct decision. It is found by calculating 1 – Beta.

A midterm exam in Applied Mathematics consist of problems in 8 topical area. One of the teachers believe that the most important of these, and the best indicator of overall performance, is the section on problem solving. She analyzes the scores of 36 randomly chosen students using MINITAB, comparing the total score to the problem-solving subscore. Give the equation for the least squares regression line. PredictorCoefStDevTP Constant ProbSolv s = 11.09R-Sq = 62.0%R-Sq (adj)= 60.9%

Find the residual amount if the observed value was (68,37). Predictor Coef SE Coef T P Constant height S = R-Sq = 80.1% R-Sq(adj) = 76.8%

She analyzes the scores of 36 randomly chosen students using MINITAB, comparing the total score to the problem-solving subscore. Find and interpret the coefficient of determination. PredictorCoefStDevTP Constant ProbSolv s = 11.09R-Sq = 62.0%R-Sq (adj)= 60.9%

She analyzes the scores of 36 randomly chosen students using MINITAB, comparing the total score to the problem-solving subscore. Find and interpret the slope. PredictorCoefStDevTP Constant ProbSolv s = 11.09R-Sq = 62.0%R-Sq (adj)= 60.9%

She analyzes the scores of 36 randomly chosen students using MINITAB, comparing the total score to the problem-solving subscore. Find an estimate for the slope. Justify your answer. PredictorCoefStDevTP Constant ProbSolv s = 11.09R-Sq = 62.0%R-Sq (adj)= 60.9%

She analyzes the scores of 36 randomly chosen students using MINITAB, comparing the total score to the problem-solving subscore. Can you justify that there is a linear relationship – using statistical justification? Show it! PredictorCoefStDevTP Constant ProbSolv s = 11.09R-Sq = 62.0%R-Sq (adj)= 60.9% Reject Ho since pval < alpha (0.05). There is a linear relationship between Problem Solving subscore and test score.

The table below specifies favorite ice cream flavors by gender. Is there a relationship between favorite flavor and gender? MaleFemale Chocolate3216 Vanilla144 Strawberry310

A study of 20 teachers in a school district indicated that the 95% confidence interval for the mean salary of all teachers in that school district is ($38,945, $41, 245). What assumptions must be true for this confidence interval to be valid? A. No assumptions are necessary. The Central Limit Theorem applies. B. The sample is randomly selected from a population of salaries that is a t-distribution. C. The distribution of the sample means is approximately normal. D. The distribution of teachers’ salaries in the school district is approximately normal. E. The standard deviation of the distribution of teachers’ salaries in the school district is known.

Can you prove that a linear relationship exists? Show it! Predictor Coef SE Coef T P Constant height S = R-Sq = 80.1% R-Sq(adj) = 76.8% Reject Ho since pval < alpha (0.05). There is a linear relationship between height and (y variable).

A study of 20 teachers in a school district indicated that the 95% confidence interval for the mean salary of all teachers in that school district is ($38,945, $41, 245). Explain what is meant by the 95% confidence interval. Explain what is meant by the 95% confidence level. We are 95% confident that the mean salary of all teachers in the school district is between $38,945 and $41,245. If we repeat this process over and over, 95% of the intervals formed will contain the true population mean.

If an NFL quarterback’s pass completion percent is 79%, what is the probability that he will only complete 15 of 30 passes in his next game?

If an NFL quarterback’s pass completion percent is 79%, what is the probability that he will only complete 15 of 30 passes in his next game? Give me two other ways of stating the formula for the previous problem.

If an NFL quarterback’s pass completion percent is 79%, what is the probability that he will only complete 15 of 30 passes in his next game? Does this problem really meet the criteria for a binomial variable? Yes – It is binomial – 2 possibilities (complete or don’t complete) Independent n is fixed success probability does not change

A candy make coats her candy with one of three colors: red, yellow, or blue, in published proportions of 0.3, 0.3, and 0.4 respectively. A simple random sample of 50 pieces of candy contained 8 red, 20 yellow, and 22 blue pieces. Is the distribution of colors consistent with the published proportions. Give appropriate statistical evidence to justify your answer. ObsExpX^ P1=prop red P2=prop yellow P3=prop blue All cells >5 Chi Sq Goodness of Fit

The primary air exchange system on a proposed spacecraft has four separate components (A, B, C, D) that all must work properly for the system to operate well. Assume that the probability of any one component working is independent of the other components. It has been shown that the probabilities of each component working are P(A) = 0.95, P(B) = 0.90, P(C )= 0.99, and P(D) = Find the probability that the entire system works properly.

The primary air exchange system on a proposed spacecraft has four separate components (A, B, C, D) that all must work properly for the system to operate well. Assume that the probability of any one component working is independent of the other components. It has been shown that the probabilities of each component working are P(A) = 0.95, P(B) = 0.90, P(C )= 0.99, and P(D) = What is the probability that at least one of the four components will work properly? The only time you don’t have at least one is when you have none. P(at least 1) = 1 – P(none) = 1 – [0.05 * 0.1 * 0.01 * 0.1] = 1 – =