STAT 205 Lecture 1: Topic_3_Chi_square_Test_student

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indigozebra246

23 Jan 2016

School

University of Calgary

Department

Statistics

Course

STAT 205

Professor

Qin Chao

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Document Summary

Understanding of the chi-square distribution and its various applications. These appli- cations include: test of population variance/standard deviation, test of homogeneity, test of independence, and goodness of t tests applied to distributions covered in statistics 213. These distributions include: uniform, binomial, poisson, and normal the normal being op- tional. 4 test for 2 2 contingency tables. The chi-square distributions are a family of distributions that take only positive values and are skewed to the right. A particular 2 distribution is speci ed by giving its degrees of freedom. We will discuss two chi-square tests: the test statistic (cid:88) (oi ei)2. Ei k where: oi = observed values (data, ei = expected values (from theory, ki = the number of di erent data cells or categories is used for the data set. This test is used to test the goodness-of- t of an assumed distribution, and the test for.

Related Questions

A salesperson makes four calls per year. A sample of 100 days given the following frequencies of sales volumes.

Number of Sales	Observed Frequency (days)
0	30
1	32
2	25
3	10
4	3
TOTAL	100

Records show sales are made to 30% of all sales calls. Assuming independent sales calls, the number of sales per day should follow a binomial distribution. The Binomial distribution is represented by:

For this exercise, assume that the population has a binomial probability distribution with n=4, p=0.30 and x= 0, 1, 2, 3 and 4.

(a) Compute the expected frequencies for x=0, 1, 2, 3 and 4 by using the binomial probability function. Combine categories if necessary to satisfy the requirement that the expected frequency is five or more for all categories.

(b) Use the goodness of fit test to determine whether the assumption of a binomial probability distribution should be rejected. Because no parameters of the Binomial probability distribution were estimated from the sample data, the degrees of freedom are k-1 .

whitebear607

1) Calculate the degrees of freedom associated with a small-sample test of hypothesis for (u1-u2), assuming o1² ≠ o2² and n1 =13, n2 = 12, s1 = 1.3, s2 = 1.5

jademoose956

(1 point) Independent random samples, each containing 900 observations, were selected from two binomial populations. The samples from populations 1 and 2 produced 632 and 665 successes, respectively.

(a) Test against ≠ 0 . Use α = 0.07