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Inferential Stats: Confidence Intervals & Hypothesis Testing for Two Population Means, Study notes of Data Analysis & Statistical Methods

An in-depth analysis of inferential statistics, specifically focusing on confidence intervals and hypothesis testing for the difference between two population means under independent sampling. The identification of the target parameter, key words and phrases, large and small sample cases, properties of the sampling distribution, and required conditions for valid inferences. It also includes formulas for confidence intervals and hypothesis testing, as well as rejection regions for one-tailed and two-tailed tests.

Typology: Study notes

Pre 2010

Uploaded on 09/02/2009

koofers-user-pvk
koofers-user-pvk 🇺🇸

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Download Inferential Stats: Confidence Intervals & Hypothesis Testing for Two Population Means and more Study notes Data Analysis & Statistical Methods in PDF only on Docsity! 10/18/2007 1 Chapter 9 Inferences Based on Two Samples: Confidence Intervals and Tests of Hypothesis Identifying the Target Parameter Parameter Key Words or Phrases Mean difference; difference in averages1 2 μ μ− 2 Difference between proportions, percentage, fractions or rates 1 2p p− Comparing Two Population Means: Independent Sampling Confidence Intervals and hypothesis testing can be done for both large and small samples 3 Large sample cases use z-statistic, small sample cases use t-statistic When comparing two population means, we test the difference between the means Comparing Two Population Means: Independent Sampling Large Sample Confidence Interval for μ1 - μ2 ( ) ( ) ( ) 2 2 2 1 221221 21 nn zxxzxx xx σσσ αα +±−=±− − 4 assuming independent sampling, which provides the following substitution 21 ( ) 2 2 2 1 2 1 2 2 2 1 2 1 21 n s n s nnxx +≈+=− σσσ Comparing Two Population Means: Independent Sampling Properties of the Sampling Distribution of (x1-x2) •Mean of Sampling distribution (x1-x2) is (μ1-μ2) •Assuming two samples are independent, the standard deviation of the sampling distribution is 5 •The sampling distribution of (x1-x2) is approximately normal for large samples by the CLT ( ) 2 2 2 1 2 1 21 nnxx σσσ +=− Comparing Two Population Means: Independent Sampling Large Sample Test of Hypothesis for μ1 - μ2 One-Tailed Test Two-Tailed Test H0:(μ1-μ2) = D0 H0:(μ1-μ2) = D0 Ha:(μ1-μ2) <D0 Ha:(μ1-μ2) ≠ D0 6 [or Ha:(μ1-μ2) >D0] Where D0 = hypothesized difference between the means Test Statistic ( ) ( )21 021 xx Dxx z − −− = σ where ( ) 2 2 2 1 2 1 21 nnxx σσ σ += − Rejection region: z < -zα Rejection region: ⏐z⏐ > zα/2 [or z > zα when Ha:(μ1-μ2) >D0]
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