Flashcards in Chap 7 Statistical Tests Deck (32):
The a priori probability of falsely rejecting the null hypothesis that the researcher is willing to accept. It is used, in conjunction with the p value, to determine whether a sample statistic is statistically significant
The alternative null hypothesis. Usually, it is the hypothesis that there is some effect present in the population ( e.g. two population means are not equal, two variables are correlated, a sample mean is diff. from a population mean, etc.).
A interval calculated using sample statistics to contain the population parameter, within a certain degree of confidence ( e.g. 95% confidence)
Statistics that describe that statistics of a given sample or population. These statistics are only meant to describe the characteristics of those from whom data were collected
A measure of the size of the effect observed in some statistic. It is a way of determining the practical significance of a statistic by reducing the impact of sample size.
Stats generated from a sample data that are used to make inferences about the characteristics of the population the sample is alleged to represent.
The hypothesis that there is no effect in the population
( e.g. that two population means are not different from each other, that 2 variables are not correlated in the population)
A test of statistical significance that is conducted just for one tail of the distribution. (e.g. that the sample mean will be larger than the population mean)
The group from which data is collected or a sample is selected. The population encompasses the entire group for which the data are alleged to apply.
A judgement about whether a statistic is relevant or of any importance, in the real world.
The probability of obtaining a statistic of a given size from a sample of a given size by chance, or due to random error.
The probability of a statistical event occurring due simply to random variations in the characteristics of the samples of a given size selected randomly from a population.
Random Sampling Error
The error, or variation, associated with randomly selecting samples of a given size from a population.
An individual or group, selected from a population, from whom of which data are collected.
When the probability of obtaining a statistic of a given size due strictly to random sampling error, or chance, is less than the selected alpha level, the result is said to be statistically. It also represents a rejection of the null hypothesis.
A test of statistical significance that is conducted just for both tails of the distribution. (e.g. that the sample mean will be different from the population mean).
Type 1 Error
Rejecting the null hypothesis when in fact the null hypothesis is true.
The p value, or the probability
The alpha level 0.5
One measure of effect size
Standard deviation used in the effect size formula
The standard error calculated with the sample standard deviation
The standard error calculated with the population standard deviation
The null hypothesis
HA or H1
The alternative hypothesis
Point estimate provides a single plausible value for a parameter
A plausible range of values for the population parameter
Note: confidence intervals only attempt to capture population parameters.
Central limit Theorem
The fact that a sample size increases, the sampling distribution of the mean becomes increasingly normal, regardless of the shape of the distribution of the sample
In a confidence interval a Margin of Error looks like what?
z* x SE
Type 2 Error
Failing to reject the null hypothesis when the alternative is true.