Example: a comparison of NOx emissions from randomly selected automobiles before and after an additive is added to the fuel. Paired or Repeated measure test: This test compares paired data, such as data collected before and after a treatment. Comparing GRE scores between men and women is an example of a two independent sample test. Two independent sample test:In this test, we collect two independent samples to test whether there is a difference in means between two populations (or if one population mean is greater or less than the other). For example, we might be interest in knowing whether the dissolved oxygen levels in a lake meet a state standard of 5 mg/L. One sample test: We make an inference to a population in comparison to some set value. In each of the tests we make inferences to a population or populations based on one or two samples. It is important to be able to differentiate between these three tests. There are three major types of comparison of means tests: (1) one sample test (2) two independent samples and (3) paired or repeated measures test. Interpret the p-value in terms of the hypotheses established prior to the test.
Determine p-value from the test statistic using the appropriate z or t distribution.ġ1. Calculate standard deviation of sample IF using a t-test.ġ0. Decide whether a z-statistic or t-statistic is appropriate.ħ. Establish null and alternative hypotheses.ĥ. Examine the appropriateness of a comparison of means test (based on the assumptions)***.Ĥ. Decide whether a one- or two-sided test.ģ. (one sample, two sample, paired samples)Ģ. General Steps in Conducting a Comparison of Means Testġ. Understand when to use the Student’s t or the z statistic in a comparison of means test. For an example of the two sample Welch’s test, click here.Ĥ.
While you will not be asked to calculate a two independent sample test statistic, you should be able to properly interpret a comparison of means test for two independent samples (understand/interpret hypotheses, test statistic and p-value). Conduct and properly interpret a one sample test.ģ. Understand the conceptual difference among a one sample, two independent sample vs. Once you have a value of from data, the graph will show you the P-value for this : it is the probability-calculated taking H 0 to be true-of getting a value at least that far away from H 0 in the direction of the arrow.1.
Try changing H a to see how the arrow changes. The blue arrow shows what kinds of values of count as evidence against H 0 in favor of your alternative H a. The normal curve shows the sampling distribution of the sample mean when your null hypothesis is true. Here we're testing a hypothesis about the mean of a normal distribution whose standard deviation we know, but the concepts are essentially the same for any other type of significance test. This applet illustrates the P-value of a test of significance. Or you can specify the true population mean μ and use the GENERATE SAMPLE button to create a random sample from the population, display the observations and sample mean (note that some of the points in the sample may be too far from μ to appear in the display), and calculate the P-value.Ĭlick the "Quiz Me" button to complete the activity.
#Standard deviation for hypothesis test calculator update#
If you already have a sample mean, enter this value and click UPDATE to display the sample mean on the graph and calculate the P-value. To set up the test, fill in the boxes: What null hypothesis H 0 about the mean μ do you want to test? Which alternative hypothesis H a do you have in mind, and what level of significance α do you require? What value of the standard deviation σ is known to be true? How many observations n will you have (250 or fewer)?
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