Hypothesis Testing/Confidence Intervals Flashcards

1
Q

Confidence Interval for p

A

a range of plausible values for p

takes the form: phat +- Margin of Error

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2
Q

ME in a confidence interval depends on…

A

Sampling Distribution

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3
Q

Confidence Interval Statement

A

We are X% confident than the true proportion of ___ lies between Z and Y.

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4
Q

What does the confidence interval tell us?

A

That we are using a method that will give us t he right answer X% of the time, not that there is a X% Probability that our confidence interval has P in it

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5
Q

Sample size calculation ask

A

How big should n be in a C% confidence interval for p so that the margin of error is a certain size?

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6
Q

Hypothesis Testing

A

A procedure based on sample evidence and probability used to test statements regarding population parameters

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7
Q

Null Hypothesis

A

Hypothesis of no change or status Quo, Presumed True unless overwhelming evidence to the contrary

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8
Q

Alternative Hypothesis

A

Hypothesis the researcher is trying to gather information in favor of. To reject the null hypothesis in favor of the alternative, overwhelming evidence must be demonstrated.

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9
Q

Errors in Hypothesis Testing

A

Rejecting Null H when it is true or not rejecting Null hypothesis when it is false. We have control over these types of errors because we decide what alpha is. Smaller values of a are reserved for situations in which making an error would have a serious consequence

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10
Q

Statistically Significant

A

When observed results are unlikely under the assumption that the null hypothesis is true then we reject the null hypothesis and we say that the result is statistically significant

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11
Q

Steps for Hypothesis Testing (general)

A
  1. Define parameter of interest in context
  2. State Null
  3. State Alternative
  4. Calculate Test Statistic
  5. Calculate P value
  6. Make decision
  7. state conclusions in context
  8. Check conditions required
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12
Q

T-distribution

A

is bell shaped like normal distribution, more spread out than normal distribution, indexed by degrees of freedom, as the degrees of freedom approach infinity, the t distribution approaches the normal

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13
Q

Matched Pairs- Dependent random samples, Case CQ

A

Suppose we have 2 dependent samples from a matched pairs design, we want to estimate the mean difference so we analyze the differences using the one sample T procudte

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14
Q

Independent Random Samples from two populations - Case CQ

A

Use equations

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15
Q

Analysis of Variance

A

ANOVA

extension of the two sample t-test

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16
Q

Are observed differences in sample means are likely to have occcured by chance just because of the random sampling?

A

Depends on the difference between the sample means and how much variability there is within each sample.

17
Q

Hypothesis Testing- ANOVA, Hnull and Ha

A

h null- all means are equal

Ha- at least on the above equalities doesn’t hold

18
Q

Case CC- inference for two proportions

A

two random samples from two populations.. We use sam,bling distribution of estimated proportions to make inferences about the p values.

19
Q

Chi Square Test of Independence Hnull and Ha

A

Hnull- variables are independent

Halt- two variables are dependent

20
Q

How do you find p value in chi square test?

A

df, read over to where the value falls in table and read up to bounds of p value on chart

21
Q

Case QQ situation

A

we have a population of (x, y) pairs from the following populations with unknown means my = a + bx with an unknown standard deviation

22
Q

Least Squares line

A

mean of case QQ. b is estimate (sigma hat) of population slope B and to make inferences about B we need to know the sampling distribution of b (represented by sigma sub b). This slope is the parameter of interest

23
Q

Confidence Interval for B statement

A

we are C% confident that the change in mean response (y) per unit increase in x lies between ___ and ___

24
Q

Case QQ Null and Alt

A
Null = slope is 0, no linear relationship between X and Y
Alt = not 0, greater than (positive linear relationship) or less than 0 (negative linear relationship)