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BaLLatris [955]
3 years ago
13

Find an explicit formula for the sequence 30\,,\,150\,,\,750\,,\,3750,...30,150,750,3750,...30, space, comma, space, 150, space,

comma, space, 750, space, comma, space, 3750, comma, point, point, point.
Mathematics
1 answer:
OverLord2011 [107]3 years ago
3 0
The series shown is an geometric series and the explicit formula is given by:
an=ar^(n-1)
where
a=first term
n=number of terms
r=common ratio
from the sequence:
a=30
r=5
thus the explicit formula will be:
an=30(5)^(n-1)
hence the answer is:
an=30(5)^(n-1)
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There is strong believe that language skills of Political science students are greater than students who study Finance. Research
BaLLatris [955]

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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Answer: 0.5

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