Unit 6 section A/B

Question 1

Parameter

Answer 1

Number of a population

Question 2

Population

Answer 2

Entire group of individuals

Question 3

To estimate or predict a population parameter, we use a

Answer 3

confidence interval

Question 4

To test a claim

Answer 4

we use a significance test

Question 5

The process that scientists and data analysts use to make that conclusion comes from a process called

Answer 5

statistical inference

Question 6

Statistic

Answer 6

The number that describe some characteristics of a sample

Question 7

Confidence Intervals

Answer 7

an interval of numbers based on our sample proportion that gives us a range where we can expect to find the true population proportion.

Question 8

A confidence interval will be based on three things:

Answer 8

sample proportion, sample size, and confidence level (usually 95%)

Question 9

sample size must be

Answer 9

large enough that we can use a normal distribution to estimate our population proportion

Question 10

As our confidence level increases, so does our __ , which in turn increases the range of our confidence interval

Answer 10

z*

Question 11

When we are given a population parameter and we have some reason to believe that it is false, we can perform a _____ test to check if that value is correct.

Answer 11

significance

Question 12

As we had with confidence intervals and sampling distributions, our significance test hinges on the fact that we must meet the three conditions of inference:

Answer 12

randomness, independence and normality.

Question 13

To check if our sampling distribution is normal, we need to verify that the expected successes and expected failures of our study is at least 10. This is known as the

Answer 13

Large Counts Condition.

Question 14

Large Counts Condition formula

Answer 14

np ≥ 10 and n(1-p) ≥ 10.

Question 15

Confidence Interval “___”

Answer 15

“We are C% confident that the interval from ____ to ____ captures the [parameter in context]” (The word “all” must be included).

Question 16

Confidence Level “__”

Answer 16

Gives the approximate % of confidence intervals that will capture the population parameter in repeated sampling in the same sample size.

“If we were to select many random samples of the same size from the same population and construct a c% confidence interval using each sample, about c% of the intervals would capture the [parameter in context]”

Question 17

Conditions

Answer 17

1. Random
2. Independence - n ≤10%N
3. Normal - using the Large Counts Condition, np and n(1-p)

Question 18

Standard error

Answer 18

An estimate of the standard deviation of the sampling distribution of p-hat

Question 19

Margin of error

Answer 19

Based on the critical value (z-score). The critical value is the number of standard deviations that the sample statistic is from the population parameter.

Question 20

One Sample z-interval for Proportions

Answer 20

An appropriate procedure for constructing a confidence interval for a single population proportion based on a sample of categorical data. Uses a z-test to estimate the population proportion based on the sample proportion and the sample size.

Question 21

The one-sample z-interval for a proportion is used when the following conditions are met:

Answer 21

1. The sample is a random sample, or the sample size is large enough (usually n > 30) to use the normal approximation to the binomial distribution.
2. The data are collected from a single categorical variable, such as a yes/no response or a dichotomous variable.
3. The sample size is large enough to use the normal approximation to the binomial distribution.
4. The population proportion is unknown and needs to be estimated from the sample data.

Question 22

Calculating the Interval: Calculating a confidence interval is based on two things:

Answer 22

our point estimate and our margin of error.

Question 23

Point Estimate

Answer 23

p-hat, The sample proportion is the estimate of the population proportion based on the sample data.