Stuff

Question 1

Mean and Standard Deviation Of a Binomial RV

Answer 1

Mean: Ux = np
Standard Deviation: ox = sqrt(np (1-p))

Question 2

Binomial Distribution (Calc Usage)

Answer 2

Exactly 5: P(X= 5) = Binompdf(n, p, 5)
At Most 5: P(X ≤ 5) = Binomedf(n, p, 5)
Less Than 5: P(X < 5) = Binomedf(n, p, 4)
At Least 5: P(X≥ 5) = 1 - Binomedf(n, p, 4)
More Than 5: P(X > 5) =1 - Binomcdf(n, p, 5)
Remember to label n, p, and X!

Question 3

Parameter vs. Statistic

Answer 3

A parameter measures a characteristic of a population, such as a population mean u or population proportion p. A statistic measures a characteristic of a sample, such as a sample mean I or sample proportion p. Statistics are used to estimate parameters.

Question 4

Geometric Setting and Random Variable

Answer 4

Arises when we perform independent trials of the same chance process and record the number of trials it takes to get one success. On each trial, the probability p of success must be the same. X= number of trials needed to achieve one success

Question 5

What is the sampling distribution of p hat?

Answer 5

Center = up = p
Spread = op = sqrt(p(1-p)/n) if n < N/10
Shape: Approx Normal if np >= 10 and n(1-p) >= 10

Question 6

What is a sampling distribution>

Answer 6

A sampling distribution is the distribution of a sample statistic in all possible samples of the same size. It describes the possible values of a statistic and how likely these values are. Contrast with the distribution of the population and the distribution of a sample.

Question 7

What is the sampling distribution of x hat?

Answer 7

Center = u hatx = u
Spread = o hatx = o/sqrt(n) if n < N/10
Shape: Normal if Pop is Normal or
Approx Normal if n >= 30 (CLT)

Question 8

What is Central Limit Theorem (CLT)?

Answer 8

If the population distribution is not Normal the sampling distribution of the sample mean & will become more and more Normal as n increases

Question 9

4 Step Process Confidence Intervals

Answer 9

STATE: What parameter do you want to estimate, and at what confidence level? PLAN: Choose the appropriate inference method. Check conditions. DO: If the conditions are met, perform calculations. CONCLUDE: Interpret your interval in the context of the problem

Question 10

Unbiased Estimator

Answer 10

A statistic is an unbiased estimator of a parameter if the mean of its sampling distribution equals the true value of the parameter being estimated. In other words, the sampling distribution of the statistic is centered in the right place. A statistic is an unbiased estimator of a parameter if the mean of its sampling distribution equals the true value of the parameter being estimated. In other words, the sampling distribution of the statistic is centered in the right place.