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Statistics
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(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

Test statistic =

Rejection region lzl >

The final conclusion is

○ A. There is not sufficient evidence to reject the null hypothesis that  

○ B. We can reject the null hypothesis that and accept that ≠ 0 

 

(b) Test  against . Use α = 0.02

Test statistic =

Rejection region z >

The final conclusion is

○ A. There is not sufficient evidence to reject the null hypothesis that

○ B. We can reject the null hypothesis that and accept that  

 

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PoksLv6
17 Aug 2021
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Related textbook solutions

Introductory Statistics
OER Edition, 2013
Openstax
ISBN: 9781938168208

Related questions

(1 point) A random sample of 130 observations is selected from a binomial population with unknown probability of success p. The computer value of is 0.64.

    (1) Test : : p = 0.65 against : p > 0.65. Use α= 0.05.

test statistic z =

critical z score

The final conclusion is 

⭕ A. We can reject the null hypothesis that p = 0.65 and accept that p is > 0.65.

⭕ B. There is not sufficient evidence to reject the null hypothesis that p = 0.65.

    (2) Test : p = 0.5 against :p < 0.65. Use α = 0.01.

test statistic z =

critical z score

The final conclusion is 

⭕ A. We can reject the null hypothesis that p = 0.5 and accept that p is < 0.5.

⭕ B. There is not sufficient evidence to reject the null hypothesis that p = 0.5.

   (3) Test : p = 0.55 against : p ≠ 0.55. Use α = 0.01.

test statistic z =

positive critical z score

 

Hypothesis testing with ANOVA opinions about whether caffeine enhances test performance differ. You design a study to test the impact of drinks with different caffeine contents on students' test-taking abilities. You choose 21 students at random from your introductory psychology course to participate in your study. You randomly assign each student to one of three drinks, each with a different caffeine concentration, such that there are seven students assigned to each drink. You then give each of them a plain capsule containing the precise quantity of caffeine that would be consumed in their designated drink and have them take an arithmetic test 15 minutes later.

The students receive the following arithmetic test scores:

  Cola Black Tea Coffee  
Caffeine Content (mg/oz) 2.9 5.9 13.4  
  85 85 92 ∑X2 = 147,641
  86 89 87 G = 1,755
  82 82 80 N = 21
  75 75 89 k = 3
  66 88 96  
  78 76 83  
  87 82 92  
  T1 = 559 T2 = 559 T3 = 559  
  SS1 = 338.86 SS2 = 338.86 SS3 = 338.86  
  n1 = 7 n2 = 7 n3 = 7  
  M1 = 79.8571 M2 = 79.8571 M3 = 79.8571  

1.) You plan to use an ANOVA to test the impact of drinks with different caffeine contents on students' test-taking abilities. What is the null hypothesis?

(a) The population mean test score for the cola population is different from the population mean test score for the black tea population.

(b) The population mean test scores for all three treatments are equal.

(c) The population mean test scores for all three treatments are different.

(d) The population mean test scores for all three treatments are not all equal.

 

2.) Calculate the degrees of freedom and the variances for the following ANOVA table:

Source SS df MS
Between - - -
Within 702.28 - -
Total 973.14 -  

 

The formula for the F-ratio is:

 

 

3.) Using words, the formula of the F-ratio can be written as:

 

 

4.) Using the data from the ANOVA table given, the F-ratio can be written as:

 

5.) Calculate for F-ratio:

 

 

6.) At the level of significance, what is your conclusion?

(a)You can reject the null hypothesis; you do not have enough evidence to say that caffeine affects test performance.

(b)You cannot reject the null hypothesis; caffeine does appear to affect test performance.

(c)You cannot reject the null hypothesis; you do not have enough evidence to say that caffeine affects test performance.

(d)You can reject the null hypothesis; caffeine does appear to affect test performance.

(1 point) Suppose a group of 900 smokers (who all wanted to give up smoking) were randomly assigned to receive an antidepressant drug or a placebo for 6 weeks. Of the 513 patients who received the antidepressant drug, 110 were not smoking one year later. Of the 387 patients who received the placebo, 101 were not smoking one year later. Given the null :   and the alternative hypothesis: ≠ 0 , conduct to see if taking an antidepressant drug can help smokers stop smoking. Use,  α= 0.05

(a) The test statistic is

(b) The P-value is

(c) The final conclusion is

    ◯ A. There seems to be evidence that the patients taking the antidepressant drug have a different success rate of not smoking after one year than the placebo group

    ◯ B. There is not sufficient evidence to determine whether the antidepressant drug has an effect on changing smoking habits after one year.

 

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