Answer:
97 in each bag
Step-by-step explanation:
485÷5=97
97*5=485
Answer:
a
The null hypothesis is ![H_o : \mu_1 = \mu_2](https://tex.z-dn.net/?f=H_o%20%3A%20%20%5Cmu_1%20%3D%20%5Cmu_2)
The alternative hypothesis ![H_a : \mu_1 > \mu_2](https://tex.z-dn.net/?f=H_a%20%3A%20%5Cmu_1%20%3E%20%20%5Cmu_2)
b
![p-value = 0.232](https://tex.z-dn.net/?f=p-value%20%20%20%3D%200.232)
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}](https://tex.z-dn.net/?f=%5C%3D%20x%20_1%20%3D%20%5Cfrac%7B%5Csum%20x_i%20%7D%7Bn%7D)
=> ![\= x _1 = \frac{7 +4 + \cdots + 6}{7}](https://tex.z-dn.net/?f=%5C%3D%20x%20_1%20%3D%20%5Cfrac%7B7%20%2B4%20%2B%20%5Ccdots%20%2B%206%7D%7B7%7D)
=> ![\= x _1 = 6.714](https://tex.z-dn.net/?f=%5C%3D%20x%20_1%20%3D%20%206.714)
Generally the sample mean for the second sample is mathematically represented as
![\= x _2 = \frac{\sum x_i }{n}](https://tex.z-dn.net/?f=%5C%3D%20x%20_2%20%3D%20%5Cfrac%7B%5Csum%20x_i%20%7D%7Bn%7D)
=> ![\= x _2 = \frac{5 + 3+ \cdots + 5}{7}](https://tex.z-dn.net/?f=%5C%3D%20x%20_2%20%3D%20%5Cfrac%7B5%20%2B%203%2B%20%5Ccdots%20%2B%205%7D%7B7%7D)
=> ![\= x _2 = 6](https://tex.z-dn.net/?f=%5C%3D%20x%20_2%20%3D%20%206)
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 } }](https://tex.z-dn.net/?f=s_1%20%3D%20%5Csqrt%7B%5Cfrac%7B%5Csum%20%28x_i%20-%20%5C%3D%20x_1%29%5E2%20%7D%7Bn-1%20%7D%20%7D)
=> ![s_1 = \sqrt{\frac{ (7 - 6.714 )^2 +(4 - 6.714 )^2 + \cdots + (6 - 6.714 )^2 }{7-1 } }](https://tex.z-dn.net/?f=s_1%20%3D%20%5Csqrt%7B%5Cfrac%7B%20%287%20-%206.714%20%29%5E2%20%2B%284%20-%206.714%20%29%5E2%20%2B%20%5Ccdots%20%2B%20%286%20-%206.714%20%29%5E2%20%7D%7B7-1%20%7D%20%7D)
=> ![s_1 = 1.905](https://tex.z-dn.net/?f=s_1%20%3D%201.905)
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 } }](https://tex.z-dn.net/?f=s_2%20%3D%20%5Csqrt%7B%5Cfrac%7B%5Csum%20%28x_i%20-%20%5C%3D%20x_2%29%5E2%20%7D%7Bn-1%20%7D%20%7D)
=> ![s_2 = \sqrt{\frac{ (5 - 6.714 )^2 +(3 - 6.714 )^2 + \cdots + (5 - 6.714 )^2 }{7-1 } }](https://tex.z-dn.net/?f=s_2%20%3D%20%5Csqrt%7B%5Cfrac%7B%20%285%20-%206.714%20%29%5E2%20%2B%283%20-%206.714%20%29%5E2%20%2B%20%5Ccdots%20%2B%20%285%20-%206.714%20%29%5E2%20%7D%7B7-1%20%7D%20%7D)
=> ![s_1 = 4.33](https://tex.z-dn.net/?f=s_1%20%3D%204.33)
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 } }](https://tex.z-dn.net/?f=s%20%3D%20%5Csqrt%7B%5Cfrac%7B%28n_1%20-%201%20%29s_1%5E2%20%2B%20%28n_2%20-%201%20%29s_2%5E2%7D%7Bn_1%20%2B%20n_2%20-2%20%7D%20%7D)
=> ![s = \sqrt{\frac{(7 - 1 )1.905^2 + (7 - 1 )4.333^2}{7 + 7 -2 } }](https://tex.z-dn.net/?f=s%20%3D%20%5Csqrt%7B%5Cfrac%7B%287%20-%201%20%291.905%5E2%20%2B%20%287%20-%201%20%294.333%5E2%7D%7B7%20%2B%207%20-2%20%7D%20%7D)
=> ![s = 1.766](https://tex.z-dn.net/?f=s%20%3D%201.766)
The null hypothesis is ![H_o : \mu_1 = \mu_2](https://tex.z-dn.net/?f=H_o%20%3A%20%20%5Cmu_1%20%3D%20%5Cmu_2)
The alternative hypothesis ![H_a : \mu_1 > \mu_2](https://tex.z-dn.net/?f=H_a%20%3A%20%5Cmu_1%20%3E%20%20%5Cmu_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}} }](https://tex.z-dn.net/?f=t%20%3D%20%5Cfrac%7B%5C%3D%20x%20_1%20-%20%5C%3D%20x_2%20%7D%7Bs%20%2A%20%5Csqrt%7B%5Cfrac%7B1%7D%7Bn_1%7D%20%2B%20%5Cfrac%7B1%7D%7Bn_2%7D%7D%20%20%7D)
=> ![t = \frac{6.714 - 6 }{1.766 * \sqrt{\frac{1}{7} + \frac{1}{7}} }](https://tex.z-dn.net/?f=t%20%3D%20%5Cfrac%7B6.714%20%20-%206%20%7D%7B1.766%20%20%2A%20%5Csqrt%7B%5Cfrac%7B1%7D%7B7%7D%20%2B%20%5Cfrac%7B1%7D%7B7%7D%7D%20%20%7D)
=> ![t = 0.757](https://tex.z-dn.net/?f=t%20%3D%200.757)
Generally the degree of freedom is mathematically represented as
![df = n_1 + n_2 - 2](https://tex.z-dn.net/?f=df%20%3D%20n_1%20%2B%20n_2%20-%202)
=> ![df = 7 + 7 - 2](https://tex.z-dn.net/?f=df%20%3D%207%20%2B%207%20-%202)
=> ![df = 12](https://tex.z-dn.net/?f=df%20%3D%2012)
From the t distribution table the probability of
at a degree of freedom of
is
![t_{ 0.757 , 12} = 0.232](https://tex.z-dn.net/?f=t_%7B%200.757%20%2C%2012%7D%20%3D%200.232)
Generally the p-value is
![p-value = t_{ 0.757 , 12} = 0.232](https://tex.z-dn.net/?f=p-value%20%20%3D%20t_%7B%200.757%20%2C%2012%7D%20%3D%200.232)
From the values obtained we see that
hence
The decision rule is
Fail to reject the null hypothesis
Answer: The greatest number of rows Li Na can plant is 9.
Step-by-step explanation:
Given: Li Na is going to plant 63 tomato plants and 81 rhubarb plants.
Li Na would like to plant the plants in rows where each row has the same number of tomato plants and each row has the same number of rhubarb plants.
To find the greatest number of rows Li Na can plant, we need to find the GCF of 63 and 81.
Since , ![63=7\times9\ and\ 81=8\times9](https://tex.z-dn.net/?f=63%3D7%5Ctimes9%5C%20and%5C%2081%3D8%5Ctimes9)
Clearly, GCF(63,81)=9
Therefore, the greatest number of rows Li Na can plant is 9.
Answer:
ok is this a troll
Step-by-step explanation:
the cake doesnot correspond to the cookie
4.true
5.false
6.true
7.true
8.true