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When is a onesample ttest used?\
Onesample ttest
When the population variance of a variable is unknown.

What is a consequence of replacing the population standard deviation with a sample standard deviation?
Onesample ttest
It changes the distribution of the test statistic. It is no longer a zdistributed but tdistributed.

What is the relationship between df and t and z distribution?
Onesample ttest
When df is small, there is a large difference between the t and z distribution. However, when df is large (i.e. greater than 30), there is no noticeable difference.

How does tcritical compare to zcritical?
Onesample ttest
tcritical will always be bigger than zcritical

Effect size
Onesample ttest
amount of difference in SD

What is estimation?
Onesample ttest
Inferential process of using statistics to estimate parameters.

Point Estimate
Onesample ttest
 a single number is used to estimate a parameter
 null hypothesis testing

Interval Estimate
Onesample ttest
a range of values is used to estimate a parameter

Confidence Interval
Onesample ttest
 when an interval estimate is accompanied by a specific level of confidence (probability)
 can be computed for any statistic

Width of Confidence Interval
Onesample ttest
 affected by confidence level and standard deviation of a statistic
  confidence level increases, width of confidence interval increases
 standard deviation of a statistic increases, width of confidence interval increases

When is an Independentsamples ttest used?
Independentsamples ttest
used to compare a mean of the DV between two groups

What is the df of independentsamples ttest?
Independentsamples ttest
 df = (n1 1) + (n2  1)
 = N2

Pooled Variance
Independentsamples ttest
weighted average of a variances of a DV for group 1 and 2

Assumptions of independentsamples ttest
Indpependentsamples ttest
 Normality
 No Outliers
 Homogeneity of Variance
 Independence of Subjects
 If violated results/conclusion of ttest could be invalid

Assumption: Normality
Independentsamples ttest
 DV should be normally distributed within each group
 tested using the ShapiroWilk

Assumption: No Outliers
Independentsamples ttest
 an outlier has an undue influence on a statistic
 assumption is checked by examining histogram and QQ plot

Assumption: Homogeneity of variance
Independentsamples ttest
the variances of the dependent variable are between group 1 and 2, Leven's test of homogeneity of variance will be used to test this assumption

Assumption: Independence of Subjects
Independentsamples ttest
 design consideration. one subject outcome is not influenced by another's outcome
 not testable

MannWhitney U
Independentsamples ttest
 Nonparametric test
 Alternative to the independentsamples ttest
 does NOT assume normality

Welch's ttest
Independentsamples ttest
 changes df to reflect violation of homogeniety
 more violated the smaller the df
 less powerful than ttest

