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252y0552 - On-line Web Courses
252y0552 - On-line Web Courses

Introduction to Statistics, Lecture 5
Introduction to Statistics, Lecture 5

... high power (usually at least 80%): Metode 3.48: The one-sample, one-sided sample size formula: For the one-sided, one-sample t-test for given α, β and σ: ...
Chapter 10 - 10.1,10.3
Chapter 10 - 10.1,10.3

Tests of Goodness of Fit and Independencec
Tests of Goodness of Fit and Independencec

... Step 5. Use the value of the test statistic and the rejection rule to determine whether to reject H0. We will reject H0 if z < - 1.96 or if z > 1.96 Because the value of the test statistic is z=1.53, the statistical evidence will not permit us to reject the null hypothesis at the .05 level of signif ...
252onesx0
252onesx0

Hypothesis Testing
Hypothesis Testing

6. Statistical Inference and Hypothesis Testing
6. Statistical Inference and Hypothesis Testing

H 0 - eLisa UGM
H 0 - eLisa UGM

...  In many cases, the alternative hypothesis focuses on one particular direction H0: μ ≤ 3 H1: μ > 3 H0: μ ≥ 3 ...
Document
Document

Significance Tests and Tests of Hypotheses
Significance Tests and Tests of Hypotheses

Course Review Chapter 9 Testing Hypotheses
Course Review Chapter 9 Testing Hypotheses

... 4. Computing the test statistic, e.g., converting the sample mean to a Z statistic or t statistic. Let’s use an example to compute the test statistic: If we assume that our sample mean family income for Native Americans is $22,400 and that our mean family income for the U.S. population is $28,985, t ...
Chapter 3: Testing Hypotheses with Data 3.1 Concepts of
Chapter 3: Testing Hypotheses with Data 3.1 Concepts of

... This logical relationship between a hypothesis H and data D means that using data can in logic only refute a hypothesis. If the data are inconsistent with the hypothesis then we know that the hypothesis is wrong. If the data are not inconsistent with the hypothesis then ... well, the hypothesis migh ...
The 2 Test Use this test when
The 2 Test Use this test when

Stats worksheet
Stats worksheet

... Biologists need to feel confidence in their results in order to say that a difference occurred due to a biological reason. They will only accept this if they have greater than 95% confidence. If they have less than 95%confidence, they are only willing to say that the difference between the results o ...
the indicated conclusion in nontechnical terms. Be sure
the indicated conclusion in nontechnical terms. Be sure

... hypothesis, alternative hypothesis, test statistic, critical value(s) or P-value, conclusion about the null hypothesis, and final conclusion that addresses the original claim. 36) The mean resting pulse rate for men is 72 beats per minute. A simple random sample of men who regularly work out at Mitc ...
Null and alternative hypotheses
Null and alternative hypotheses

... made (b) state a very clear rule for making the decision, and (c) compute the necessary information to use this clear and unambiguous decision rule. First, let's see how researchers define their decisions as a choice between two options: a null hypothesis and an alternative hypothesis. ...
Analysis and Presentation of Behavioral Data
Analysis and Presentation of Behavioral Data

Hypothesis Testing: Single Mean and Single Proportion
Hypothesis Testing: Single Mean and Single Proportion

UNIT - III TESTING OF HYPOTHESIS A statistical hypothesis is an
UNIT - III TESTING OF HYPOTHESIS A statistical hypothesis is an

Test - WordPress.com
Test - WordPress.com

... Definition : Critical probability or critical level or Pvalue of hypothesis H0 ,  *, is the level of test at which one rejects H0 given the results of observations. The critical level  * depends on the results of observations and test that uses. Knowing the critical level  *, we can say what deci ...
§9.3--Hypothesis Tests for One Population Mean When is Known
§9.3--Hypothesis Tests for One Population Mean When is Known

... The alternative hypothesis will be of one of three forms: left-tailed, two-tailed, or right-tailed. We are assuming that the null hypothesis is true and we are looking for evidence to the contrary. We will reject H0 only when the evidence suggests that something improbable has occurred. The signific ...
Inference about a Mean Vector
Inference about a Mean Vector

... - Use the Decision Rule to Evaluate the Test Statistic and Decide Whether to Reject or Not Reject the Null Hypothesis –1.761  t  1.761, i.e., –1.761  -1.748  1.761 so do not reject H0. At a = 0.10. the sample evidence does not refute the claim that the mean of X2 is -1.5. ...
Overview Hypothesis Testing Hypothesis Testing
Overview Hypothesis Testing Hypothesis Testing

H 0
H 0

... “unlikely”, so-called “the level of significance” • “Unlikely” means that this difference occurs with probability α = 0.05 of the time, or less under the null hypothesis • This concept applies to two-tailed tests, left-tailed tests, and right-tailed tests Note: α is often determined subjectively bef ...
Estimation V
Estimation V

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Statistical hypothesis testing

A statistical hypothesis is a hypothesis that is testable on the basis of observing a process that is modeled via a set of random variables. A statistical hypothesis test is a method of statistical inference. Commonly, two statistical data sets are compared, or a data set obtained by sampling is compared against a synthetic data set from an idealized model. An hypothesis is proposed for the statistical relationship between the two data sets, and this is compared as an alternative to an idealized null hypothesis of no relationship between two data sets. The comparison is deemed statistically significant if the relationship between the data sets would be an unlikely realization of the null hypothesis according to a threshold probability—the significance level. Hypothesis tests are used in determining what outcomes of a study would lead to a rejection of the null hypothesis for a pre-specified level of significance. The process of distinguishing between the null hypothesis and the alternative hypothesis is aided by identifying two conceptual types of errors (type 1 & type 2), and by specifying parametric limits on e.g. how much type 1 error will be permitted.An alternative framework for statistical hypothesis testing is to specify a set of statistical models, one for each candidate hypothesis, and then use model selection techniques to choose the most appropriate model. The most common selection techniques are based on either Akaike information criterion or Bayes factor.Statistical hypothesis testing is sometimes called confirmatory data analysis. It can be contrasted with exploratory data analysis, which may not have pre-specified hypotheses.
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