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Unformatted text preview: hesis Testing for One Population Mean
Comparing Two Means for Two Independent Populations
Comparing Two Means for Two Dependent Populations The ttable Conﬁdence Intervals and Hypothesis Testing for Population Hypothesis Testing for Population Means Hypothesis Testing for One Population Mean
Comparing Two Means for Two Independent Populations
Comparing Two Means for Two Dependent Populations Using the ttable How to use the t − table :
http://www.youtube.com/watch?v=tI6mdx3s0zk Conﬁdence Intervals and Hypothesis Testing for Population Hypothesis Testing for Population Means Hypothesis Testing for One Population Mean
Comparing Two Means for Two Independent Populations
Comparing Two Means for Two Dependent Populations Conﬁdence Interval
S
x ± tα /2,n−1 · √
¯
n Conﬁdence Intervals and Hypothesis Testing for Population Hypothesis Testing for Population Means Hypothesis Testing for One Population Mean
Comparing Two Means for Two Independent Populations
Comparing Two Means for Two Dependent Populations Example Conﬁdence Intervals and Hypothesis Testing for Population Hypothesis Testing for Population Means Hypothesis Testing for One Population Mean
Comparing Two Means for Two Independent Populations
Comparing Two Means for Two Dependent Populations Overview of Comparing Two Means Consider two populations (groups) having means
2
2
and variances (µ1 , σ1 ) and (µ2 , σ2 ) respectively.
We are interested in the comparing the means
µ1 − µ2 .
Suppose two samples of size n1 and n2 are drawn
independently from each population.
2
¯
¯
Let Y1 and Y2 denote the sample means and s1
2
and s2 denote the sample variances.
¯
For large samples, the random variables, Y1 and
¯
Y2 , are approximately normal.
¯
¯
Thus the random variable Y1 − Y2 is also
Conﬁdence
approximately normal, that is Intervals and Hypothesis Testing for Population Hypothesis Testing for Population Means Hypothesis Testing for One Population Mean
Comparing Two Means for Two Independent Populations
Comparing Two Means for Two Dependent Populations Assumptions and Conditions
Independence Assumption:
Randomization: the data are collected randomly
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This test prep was uploaded on 03/12/2014 for the course STATS 10 taught by Professor Ioudina during the Spring '08 term at UCLA.
 Spring '08
 Ioudina

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