stat

• What does the effect size tell you

A measure of effect size is intended to provide a measurement of the absolute magnitude of treatment effect, independent of the size of the sample (S) being used.

What does the standard error for the z-mean statistic indicate

Standard error is how much of a difference we expect between are sample mean and the population mean due to random chance (based on n and Q)

How does the standard error impact the results of a hypothesis test

The larger the standard deviation the more variability, larger standard error. If you increase the sample size, increases z score, standard error decreases.

z-test for sample mean

single sample compared to population (σ is known)

t-test for single sample

single sample compared to population (σ is unknown)

t-test for related samples

the same sample being measured twice or two matched samples (no information on the population)

What is the content of the sampling distribution

Is a distribution of statistics obtained by selecting all of the possible samples of a specific size from a population. (mean, standard error and shape)

In general, what is a two-tailed test?

A statistical test in which the critical area of a distribution is two sided and tests whether a sample is either greater than or less than a certain range of values. If the sample that is being tested falls into either of the critical areas, the alternative hypothesis will be accepted instead of the null hypothesis. The two-tailed test gets its name from testing the area under both of the tails (sides) of a normal distribution, although the test can be used in other non-normal distributions.

What does the alpha level indicate

The alpha level or the level of significance, is probability value that is used to define the concept of " very unlikely" in a hypothesis test. The alpha level is a small probability that is used to identify the low probability samples. .05=5 % chance, .01=1% chance. For example .05 we separate the most unlikely 5% of the sample means (the extreme values) from the most likely 95 % of sample means (the central values). The extremely unlikely values, as defined by the alpha level make up what is called a critical region. Not consistent with the null hypothesis. Very unlikely to occur if the null hypothesis is true. When a sample mean that is located in the critical region, we conclude that the data is not consistent with the null hypothesis, and we reject the null hypothesis.

What is type I error

Type I error occurs when a researcher rejects a null hypothesis that is actually true. In a typical research situation, a Type 1 error means that the researcher concludes that a treatment does not have an effect when, in fact, it has no effect. Type error 1 can be very serious because the researcher has rejected the null hypothesis and believes that the treatment has a real effect, it is likely that the researcher will report or even publish the research results. A false report.

In general, what is a two-tailed test?

A two-test tailed requires a relatively large difference independent of direction. Two-tailed test demands more evidence to reject H0. Difficult to reject the H0. Should be used when there is no strong directional expectation or when there are two competing predictions.

What does the standard error for the t-related samples statistic indicate

Controls for individual differences and eliminates the standard error due to individual differences not related to the IV. Don't need a large sample size standard error is going to be much smaller when using related subject.

In general, what is a one-tailed test?

Directional hypothesis test, or a one-tailed test, the statistical hypothesis (H) and H1) specify either an increase or a decrease in the population mean. That is they make a statement about the direction of the effect.

In general, what is the null hypothesis

H0, states that in the general population there is no change, no difference, or no relationship. In the context of an experiment, H0 predicts that the independent variable (treatment) has no effect on the dependent variable (scores) for the population.

How do you state the null hypothesis (in symbols) for t-tests?

H0:u=500 not significantly different or no change or equal to H0:u≤500 decrease or have no significant effect H0:u≥500 increase or have no significant effect

In general, what is the alternative hypothesis

H1, states that their is a change, a difference, or a relationship for the general population. In the context of an experiment, H1 predicts that the independent variable (treatment) does have an effect on the dependent variable.

How do you state the alternative hypothesis (in symbols) for t-tests?

H1:u≠ 500 the mean test score is different from 500 ( no increase or decrease) significant effect H1:u>500 significantly increase in test scores H1:u<500 significantly decrease in test scores

What does "significant" mean?

Significant or statistically significant, if it is very unlikely to occur when the null hypothesis is true. That is the result is sufficient to reject the null hypothesis. Thus, a treatment has a significant effect if the decision from the hypothesis test is to reject the H0.

What does the standard error for the t-single sample statistic indicate

T is used for single sample hypothesis testing when there is no information about the variability of scores in the population.

How does the alpha level impact the results of a hypothesis test

The alpha level for a hypothesis test is the probability that the test will lead to a type 1 error if the null hypothesis is true. That is the alpha level determines the probability of obtaining sample data in the critical region even though their is no treatment effect.

What is type II error

Type II error occurs when a researcher fails to reject a null hypothesis that is really false. In typical research situation, a type II error means that the hypothesis test has failed to detect a real treatment effect. The concern is that the research data does not show the result the researcher hoped to obtain.