Pls answer

Suppose a marketing company wants to determine the current proportion of customers who click on ads on their smartphones. It was

Zolol [24]

Answer: 10 customers.

Step-by-step explanation:

The formula to find the required sample size :

$n=p(1-p)(\dfrac z^*}{E})^2$ (1)

, where p= prior population proportion.

n= sample size.

$\sigma$ = Population standard deviation from previous studies.

Let p be prior population proportion of the customers who click on ads on their smartphones .

As per given , we have

p=0.62

E= 0.27

For 92% confidence , significance level : $\alpha=1-0.92=0.08$

The critical value of z for 92% confidence interval from z-table would be

$z_{\alpha/2}=z_{0.04}=1.75$

Put theses values in the formula (1), we will get

$n=(0.62)(1-0.62)(\dfrac{(1.75)}{0.27})^2$

$n=(0.2356)(6.48148)^2= 9.89745775254\approx 10$

Therefore , the company should survey 10 customers .

6 0

3 years ago

Tess rolls 2 fair dice. <br> What is the probability of obtaining two 4's?

harina [27]

Answer:

1/36

Step-by-step explanation:

Since Tess rolled 2 different dices, there are 36 different possibilities. Rolling two 4's is 1 of them.

Therefore, the probability of Tess rolling 2 fair dice is 1/36

Hope this helped have a great rest of your day!

4 0

3 years ago

Read 2 more answers

Suppose that you play the game with three different friends separately with the following results: Friend A chose scissors 100 t

Yanka [14]

Answer:

Friend A

$\hat p_A= \frac{100}{400}=0.25$

$z=\frac{0.25 -0.333}{\sqrt{\frac{0.333(1-0.333)}{400}}}\approx -3.47$

Friend B

$\hat p_B= \frac{20}{120}=0.167$

$z=\frac{0.167 -0.333}{\sqrt{\frac{0.333(1-0.333)}{120}}}\approx -3.80$

Friend C

$\hat p_C= \frac{65}{300}=0.217$

$z=\frac{0.217-0.333}{\sqrt{\frac{0.333(1-0.333)}{300}}}\approx -4.17$

So then the best solution for this case would be:

-3.47 (100 out of 400; 25%), -3.80 (20 out of 120; 16.7%), -4.17 (65 out of 300; 21.7%)

Step-by-step explanation:

Data given and notation

n represent the random sample taken

X represent the number of scissors selected for each friend

$\hat p=\frac{X}{n}$ estimated proportion of scissors selected for each friend

$p_o=\frac{1}{3}=0.333$ is the value that we want to test

$\alpha$ represent the significance level

z would represent the statistic (variable of interest)

$p_v$ represent the p value (variable of interest)

Concepts and formulas to use

We need to conduct a hypothesis in order to test the claim that the proportion that the friend will pick scissors is less than 1/3 or 0.333, the system of hypothesis would be:

Null hypothesis: $p\geq 0.333$

Alternative hypothesis: $p < 0.333$

When we conduct a proportion test we need to use the z statistic, and the is given by:

$z=\frac{\hat p -p_o}{\sqrt{\frac{p_o (1-p_o)}{n}}}$ (1)

The One-Sample Proportion Test is used to assess whether a population proportion $\hat p$ is significantly different from a hypothesized value $p_o$ .