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svetlana [45]
3 years ago
6

A family block of Chocolate is made up of 6o small squares

Mathematics
1 answer:
zubka84 [21]3 years ago
3 0

Answer:

a family block of Chocolate is made up of 6o small squares

manica eats 10 square John eats 9 Squares and holly eats

5 squares what is the fraction of the block of chocolate

is left

Step-by-step explanation:

i think its answer is 36

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AT&T would like to test the hypothesis that the proportion of 18- to 34-year-old Americans that own a cell phone is less tha
Vera_Pavlovna [14]

Answer:

The null and alternative hypothesis can be written as:

H_0: \pi_1-\pi_2=0\\\\H_a:\pi_1-\pi_2< 0

Step-by-step explanation:

This is a hypothesis test for the difference between proportions.

The claim is that the proportion of 18- to 34-year-old Americans that own a cell phone is less than the proportion of 35- to 49-year-old Americans.

This claim will be reflected in the alternnative hypothesis, that will state that the population proportion 1 (18 to 34) is significantly smaller than the population proportion 2 (35 to 49).

On the contrary, the null hypothesis will state that the population proportion 1 is ot significantly smaller than the population proportion 2.

Then, the null and alternative hypothesis can be written as:

H_0: \pi_1-\pi_2=0\\\\H_a:\pi_1-\pi_2< 0

The significance level is assumed to be 0.05.

The sample 1, of size n1=200 has a proportion of p1=0.63.

p_1=X_1/n_1=126/200=0.63

The sample 2, of size n2=175 has a proportion of p2=0.68.

p_2=X_2/n_2=119/175=0.68

The difference between proportions is (p1-p2)=-0.05.

p_d=p_1-p_2=0.63-0.68=-0.05

The pooled proportion, needed to calculate the standard error, is:

p=\dfrac{X_1+X_2}{n_1+n_2}=\dfrac{126+119}{200+175}=\dfrac{245}{375}=0.653

The estimated standard error of the difference between means is computed using the formula:

s_{p1-p2}=\sqrt{\dfrac{p(1-p)}{n_1}+\dfrac{p(1-p)}{n_2}}=\sqrt{\dfrac{0.653*0.347}{200}+\dfrac{0.653*0.347}{175}}\\\\\\s_{p1-p2}=\sqrt{0.001132+0.001294}=\sqrt{0.002427}=0.049

Then, we can calculate the z-statistic as:

z=\dfrac{p_d-(\pi_1-\pi_2)}{s_{p1-p2}}=\dfrac{-0.05-0}{0.049}=\dfrac{-0.05}{0.049}=-1.01

This test is a left-tailed test, so the P-value for this test is calculated as (using a z-table):

\text{P-value}=P(z

As the P-value (0.1554) is bigger than the significance level (0.05), the effect is not significant.

The null hypothesis failed to be rejected.

There is not enough evidence to support the claim that the proportion of 18- to 34-year-old Americans that own a cell phone is less than the proportion of 35- to 49-year-old Americans.

5 0
3 years ago
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