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dusya [7]
3 years ago
10

There is strong believe that language skills of Political science students are greater than students who study Finance. Research

er selected some students from each faculty in order to assess this claim by using 95% confidence level. Language exam was taken from students for this purpose. It is assumed than unknown population variance of language skills for each faculty is the same. Exam results are given in the following table.
Observation Political Science Finance
1 7 5
2 4 3
3 8 7
4 8 8
5 7 9
6 7 5
7 6 5

a) Formulate Null and Alternative Hypothesis. (1 point)
b) Calculate p value of the test. (4 points)
c) What is your decision about Hypothesis? (2 points
Mathematics
1 answer:
BaLLatris [955]3 years ago
8 0

Answer:

a

The null hypothesis is  H_o :  \mu_1 = \mu_2

The alternative hypothesis  H_a : \mu_1 >  \mu_2

b

p-value   = 0.232

c

    The decision rule is  

Fail to reject the null hypothesis

Step-by-step explanation:

From the question we are told that

  The value given is  

S/N

1       7 5

2      4 3

3      8 7

4      8 8

5      7 9

6      7 5

7      6 5

Generally the sample mean for the first sample  is  mathematically represented as

        \= x _1 = \frac{\sum x_i }{n}

=>     \= x _1 = \frac{7 +4 + \cdots + 6}{7}

=>     \= x _1 =  6.714

Generally the sample mean for the second sample is mathematically represented as

        \= x _2 = \frac{\sum x_i }{n}

=>     \= x _2 = \frac{5 + 3+ \cdots + 5}{7}

=>     \= x _2 =  6

Generally the sample standard deviation  for the first sample  is  mathematically represented as

           s_1 = \sqrt{\frac{\sum (x_i - \= x_1)^2 }{n-1 } }

=>       s_1 = \sqrt{\frac{ (7 - 6.714 )^2 +(4 - 6.714 )^2 + \cdots + (6 - 6.714 )^2 }{7-1 } }

=>       s_1 = 1.905

Generally the sample standard deviation  for the second  sample  is  mathematically represented as

           s_2 = \sqrt{\frac{\sum (x_i - \= x_2)^2 }{n-1 } }

=>       s_2 = \sqrt{\frac{ (5 - 6.714 )^2 +(3 - 6.714 )^2 + \cdots + (5 - 6.714 )^2 }{7-1 } }

=>       s_1 = 4.33

Generally the pooled standard deviation is  

      s = \sqrt{\frac{(n_1 - 1 )s_1^2 + (n_2 - 1 )s_2^2}{n_1 + n_2 -2 } }

=>    s = \sqrt{\frac{(7 - 1 )1.905^2 + (7 - 1 )4.333^2}{7 + 7 -2 } }

=>    s = 1.766

The null hypothesis is  H_o :  \mu_1 = \mu_2

The alternative hypothesis  H_a : \mu_1 >  \mu_2

Generally the test statistics is mathematically represented as

      t = \frac{\= x _1 - \= x_2 }{s * \sqrt{\frac{1}{n_1} + \frac{1}{n_2}}  }

=>   t = \frac{6.714  - 6 }{1.766  * \sqrt{\frac{1}{7} + \frac{1}{7}}  }

=>   t = 0.757

Generally the degree of freedom is mathematically represented as

     df = n_1 + n_2 - 2

=>   df = 7 + 7 - 2

=>   df = 12

From the t distribution table the probability of  t = 0.757 at a degree of freedom of df = 12 is  

     t_{ 0.757 , 12} = 0.232

Generally the p-value is  

      p-value  = t_{ 0.757 , 12} = 0.232

From the values  obtained we see that p-value >  \alpha  hence  

   The decision rule is  

Fail to reject the null hypothesis

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