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2012
Previous chapters have presented information on sampling distributions, Central Limit Theorem, confidence intervals, TYPE I error, TYPE II error, and hypothesis testing. This information is useful in understanding how sample statistics are used to test differences between population parameters.
Randall Schumacker, Sara Tomek
openaire +2 more sources
Previous chapters have presented information on sampling distributions, Central Limit Theorem, confidence intervals, TYPE I error, TYPE II error, and hypothesis testing. This information is useful in understanding how sample statistics are used to test differences between population parameters.
Randall Schumacker, Sara Tomek
openaire +2 more sources
2021
In the simplest type of situation considered in this chapter, each observation in a sample is classified as belonging to one of a finite number of categories—for example, blood type could be one of the four categories O, A, B, or AB. With pi denoting the probability that any particular observation belongs in category i, we wish to test a null ...
Jay L. Devore +2 more
openaire +2 more sources
In the simplest type of situation considered in this chapter, each observation in a sample is classified as belonging to one of a finite number of categories—for example, blood type could be one of the four categories O, A, B, or AB. With pi denoting the probability that any particular observation belongs in category i, we wish to test a null ...
Jay L. Devore +2 more
openaire +2 more sources