Answer:
a) p-hat (sampling distribution of sample proportions)
b) Symmetric
c) σ=0.058
d) Standard error
e) If we increase the sample size from 40 to 90 students, the standard error becomes two thirds of the previous standard error (se=0.667).
Step-by-step explanation:
a) This distribution is called the <em>sampling distribution of sample proportions</em> <em>(p-hat)</em>.
b) The shape of this distribution is expected to somewhat normal, symmetrical and centered around 16%.
This happens because the expected sample proportion is 0.16. Some samples will have a proportion over 0.16 and others below, but the most of them will be around the population mean. In other words, the sample proportions is a non-biased estimator of the population proportion.
c) The variability of this distribution, represented by the standard error, is:
d) The formal name is Standard error.
e) If we divided the variability of the distribution with sample size n=90 to the variability of the distribution with sample size n=40, we have:
If we increase the sample size from 40 to 90 students, the standard error becomes two thirds of the previous standard error (se=0.667).
Linear regression line y=2.1x+130 predicts sales based on the money spent on advertising.
Linear regression represents the relationship between two variables. the value of y depends on the value of x.
x represents the dollars spent in advertising and y represents the company sales in dollars.
We need to find out sales y when $150 spends on advertising.
Plug in 150 for x and find out y
y = 2.1 x + 130
y = 2.1 (150) + 130
y= 445
The company expects $445 in sales
Answer:
85%
Step-by-step explanation:
Convert fraction (ratio) 170 / 200 Answer: 85%