Stat 201 Exam 2 Study Guide
Stat 201 Exam 2 Study Guide STAT 201
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This 4 page Study Guide was uploaded by AlliSlaten on Tuesday October 18, 2016. The Study Guide belongs to STAT 201 at Colorado State University taught by Kirk Ketelsen in Fall 2016. Since its upload, it has received 100 views.
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Date Created: 10/18/16
How to ﬁnd the conﬁdence interval • Conﬁdence Interval- an estimate of a mean gives a range of the most plausible values of the true mean. • Bigger interval means higher conﬁdence level • Formula How to ﬁnd the t-test statistic • This value is what is compared to the t-value when determining whether or not it rejects or fails to reject Ho What is the Critical value and how do you ﬁnd it on the T-chart? 1. Along the top go to the alpha value which is given by the problem and is determined based on whether or not the problem is one tailed or two tailed. 2. Along the left side ﬁnd your degree of freedom which is n-1 3. See where they meet and this is your t- value How to determine if the test if one tail or two tailed • To determine whether or not the test is one tailed or two tailed look at the null hypothesis and the signs. If the signs are greater than, greater than or equal to, less than, or less than or equal to, the test is one tailed. If the test has an equal sign and not equal the test is two tailed. How to determine which way the signs face for the null hypothesis and the alternate right tailed—> mu > x • • left tailed —> mu < x • How do you know if the value reject or fails to reject? • If the value is in the shaded region the value rejects Ho, if the value is in the white zone the value FTR (fails to reject) Ho How to interpret the data and make a statistical decision • The test rejects if the value is in the shaded area this would be worded as “# rejects Ho”. • If the value is in the white area it would be worded as “# FTR (fails to reject) Ho” How to calculate the P- value • on the calculator —> • Right tailed—> tcdf(value, 100, degree of freedom) Left tailed —> tcdf(-11,value, degree of freedom) • Hypothesis testing • Used to determine if we have enough evidence to reject a null hypothesis (Ho) in favor of an alternative hypothesis (Ha) • Equal sign ALWAYS goes with the null hypothesis (Ho). This can be grater than or equal to, less than or equal to, or just equal to • 1. Set up the null hypothesis and alternative hypothesis • 2. State the signiﬁcance level and the corresponding critical value • 3. Compute the t-test statistic and p-value 4. Make the statistical decision and interpret your results • Margin of Error Dependent Sample t-test (2 sets of data) • Find the difference of the before and after to get your new data set • Two tailed —> P-value is tcdf X 2 • Ho: mu1 = mu2 • Ha: mu1 DOES NOT EQUAL mu2 • T- test formula Example Problem •
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