Lecture 10: Hypothesis Testing Flashcards

1
Q

Probability

A

the relative likelihood of an event occurring

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2
Q

probability is measured on

A

a scale from 0 (absolute certainty the event will not occur) to 1 (absolute certainty the event will occur
*sometimes discussed in terms of a %

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3
Q

normal probability distribution

A

a density function which assumes a bell-shaped curve

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4
Q

significance

A
  • many random variables observed in nature have a frequency that follows a bell shape.
  • provides a large sample approximation to the probability distributions for many estimators and test statistics.
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5
Q

significance allows us

A

to make inferences about the population from which our samples are drawn

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6
Q

Central Limit Theorem

A

in random samples of N, observations drawn from a population with a mean (u), SD (sigma), the samples means will be approx. normally distributed with a mean equal to U and a SD = sigma/SQRT(N) (SEM)

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7
Q

similarities between t-distribution curve and normal distribution

A

t-distribution - family of curves.

-both mound-shaped and symmetrical

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8
Q

difference between t-distribution and normal distribution curve

A

t-distribution changes shape as a function of the sample size - the “tails” become thicker as N decreases

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9
Q

confidence interval

A

constructed around our point estimate of the population mean.
- consists of a lower confidence bound and an upper confidence bound with the population mean contained within this interval (1-alpha) percent of the time

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10
Q

sample mean

A

an unbiased estimator for the population mean

*this estimate, by itself, gives us no idea of its accuracy

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11
Q

research hypothesis

A

a prediction based on the theory being tested; on preliminary observations; on contentions or guesses.

a language-based statement of what we are trying to prove

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12
Q

research hypothesis example

A

gender affects intelligence eye roll

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13
Q

Null hypothesis

A

a mathematical statement, usually in population parameters, of no difference
-can be expressed as a function of the parameters equaling zero, hence term “null”

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14
Q

null hypothesis example

A

u(men) - u (female) = 0

u(men) = u(female)

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15
Q

alternative hypothesis

A

an objective mathematical statement of the research hypothesis similar to the null hypothesis
- we PROVE the alternative hypothesis by showing that the null is unlikely to be true

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16
Q

alternative hypothesis example

A

u(male) - u(female) does not = 0