Answer to Question #226075 in Statistics and Probability for Carrie

Question #226075

Consider a multinomial experiment involving n D 300 and that the observed frequencies are given

in the following table:

Cell 1 2 3 4

Frequency 76 100 76 48

The investigator wants to test the null hypothesis: H0 : p1 D 0:3; p2 D 0:3; p3 D 0:2; p4 D 0:2:

The test statistic is

1. 302

2. 6:0786

3. 0:9876

4. 1

5. 9:9556


1
Expert's answer
2021-09-03T07:48:45-0400
"\\def\\arraystretch{1.5}\n \\begin{array}{c:c:c:c:c}\n Cell & 1 & 2 & 3 & 4 \\\\ \\hline\n Frequency & 76 & 100 & 76 & 48 \\\\\n \\hdashline\n \n\\end{array}"



The null hypothesis to be tested is as follows:

"H_0 : p_1 = 0.3, p_2 = 0.3, p_3 = 0.2, p_4 = 0.2"

We seek a test statistic that will detect a lack of fit of the observed cell counts to our hypothesized (null) expected cell counts based on the hypothesized cell probabilities.

These expected values are:


"E(n_1)=np_1=300(0.3)=90"

"E(n_2)=np_2=300(0.3)=90"

"E(n_3)=np_3=300(0.2)=60"

"E(n_4)=np_4=300(0.2)=60"

"\\chi^2=\\displaystyle\\sum_{all\\ cells}\\dfrac{(observed-expected)^2}{expected}=\\displaystyle\\sum_{i}\\dfrac{(n_i-E(n_i))^2}{E(n_i)}"

"\\chi^2=\\dfrac{(76-90)^2}{90}+\\dfrac{(100-90)^2}{90}+\\dfrac{(76-60)^2}{60}+\\dfrac{(48-60)^2}{60}"


"\\chi^2=\\dfrac{196}{90}+\\dfrac{100}{90}+\\dfrac{256}{60}+\\dfrac{144}{60}"

"\\chi^2=\\dfrac{448}{45}"

"\\chi^2\\approx9.9556"

5. "9.9556"




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