Chapter 7 One Sample And Dependent Sample T Test

Front 1

One Sample T-test

Back 1

don't know population standard deviation, use our sample to estimate the population standard deviation

Front 2

Sampling dist. of population variance

Back 2

positively skewed because we underestimate the pop standard deviation, to get it closer to normal we take a large sample --> 120 and up.

Front 3

T-distribution properties

Back 3

based off of degrees of freedom.

For each degree of freedom there is a separate t-distribution.

compare our results to t-distribution

Front 4

T-distribution (continued) achieving accurate results

Back 4

the larger the df, smaller the spread of dist.

the smaller the df, the wider the spread of dist.

using a larger distribution means better results

Front 5

finding one sample t-value

Back 5

we replace the pop. mean in the equation with the standard deviation of the sample.

Front 6

Confidence intervals for one sample t-test

Back 6

we are .95 sure that the pop mean is or is not included in the upper and lower levels

Front 7

Dependent Means T-test

Back 7

Telling the difference between time 1 and 2. No population

use control and experimental conditions or time 1 and 2

Front 8

Difference formula

Back 8

time 1 - time 2

Front 9

Null and Alt. Hypothesis dependent samples

Back 9

MD = 0

MD doesn't equal 0

Front 10

Difference data

Back 10

Take the difference between time 1 and 2 and conduct a normal t-test on it. Then look up the t-value and compare. Were trying to find out if there's a difference, so it needs to be statistically different from 0.

Front 11

Confidence Intervals

Back 11

mean of the difference +/- t-value(SD)

if 0 (the value of the dist. of the mean dif. mean) is not in between these two values you reject the null.

Front 12

Null and Alt. Hypothesis one samples

Back 12

sample mean = population mean

sample mean does not equal population mean