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Hypothesis Testing: Significance of Differences in Proportions and Chi-Square Statistic, Lecture notes of Social Statistics and Data Analysis

Nipissing UniversitySocial Statistics and Data Analysis

An overview of hypothesis testing, focusing on the significance of differences in proportions and the use of the chi-square statistic for testing hypotheses with nominal or ordinal variables. It covers the steps involved in testing a statistical hypothesis, including formulating the research and null hypotheses, selecting the appropriate test statistic, and deciding whether to reject the null hypothesis based on the calculated and critical values.

Typology: Lecture notes

2011/2012

Uploaded on 01/26/2012

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Hpothesis Testing of Proportions:
•In most research, we want to test hypotheses
about the differences between two or more groups
or levels of a variable.
•For example, you are studying the efficacy of a
new drug for treating AIDS. One group of patients
receives the existing drug of choice: the other
group receives a new drug. After 12 months you
find…..
New Drug Old Drug
Proportion surviving = .75 .70
Initial Sample Size = 100 100
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Download Hypothesis Testing: Significance of Differences in Proportions and Chi-Square Statistic and more Lecture notes Social Statistics and Data Analysis in PDF only on Docsity!

Hpothesis Testing of Proportions:

  • In most research, we want to test hypotheses about the differences between two or more groups or levels of a variable.
  • For example, you are studying the efficacy of a new drug for treating AIDS. One group of patients receives the existing drug of choice: the other group receives a new drug. After 12 months you find…..

New Drug Old Drug Proportion surviving = .75. Initial Sample Size = 100 100

  • Although the findings are promising, we must test if the difference in the proportion surviving is statistically significant.
  • A statistically significant difference implies that the difference in the proportion surviving using the old & new drugs is so large that we can rule out chance or random sampling error as explanations for the difference.
  • A significant difference means the new AIDS drug has a real, beneficial effect on survival.

Steps in testing a statistical

hypothesis:

  • Formulate the Research Hypothesis (H 1 :)
  • Formulate the Null Hypothesis (H 0 :)
  • Select the appropriate test statistic

Steps in testing a statistical

hypothesis:

  • Formulate the Research Hypothesis (H 1 :)
  • Formulate the Null Hypothesis (H 0 :)
  • Select the appropriate test statistic
  • Choose level of significance (e.g., sig. = .05, .01, .001)
  • Decide if you can reject the Null Hypothesis (H 0 :)