Answer:
A: enlargement B: 2
Step-by-step explanation:
im pretty sure this is correct
Answer:
a
The null hypothesis is 
The alternative hypothesis is 
b

c

d
There no sufficient evidence to support the conclusion that the population mean sales prices for new one-family homes in the South is less expensive than the national mean of $181,900
Step-by-step explanation:
From the question we are told that
The population mean is 
The sample size is 
The sample mean is
The sample standard deviation is 
The null hypothesis is 
The alternative hypothesis is 
Generally the test statistics is mathematically represented as

=> 
=> 
Generally the p-value is obtain from the z-table the value is

=> 
From the calculation we see that
hence we fail to reject the null hypothesis
Thus there no sufficient evidence to support the conclusion that the population mean sales prices for new one-family homes in the South is less expensive than the national mean of $181,900
Answer:
your answer will be D
Step-by-step explanation:
look at the graph and find a corner by the black line there is a corner by -2 and positive 2
Answer:
2.27%
Step-by-step explanation:
Lets start by making the names letters, J C and A respectively.
The total is 44 dollars. J paid 34%, which would be 14.96. He pays a total of $15. C paid 50%, which is 22 dollars. A pays 17%, which would be 7.48. She pays a total of $8.
15 + 8 + 22 = $45, meaning they paid an extra 1 dollar. One dollar is 1/44th of $44, or 2.27%.
Note: 2.27% is 2.272727272727 repeated, do what you will with that information, every site is different.
Answer:
0.64 = 64% probability that two randomly sampled new employees will both be able to survive their first year
Step-by-step explanation:
For each employee, there are only two possible outcomes. Either they survive the first year, or they do not. The probability of an employee surviving the first year is independent of other employees. This means that we use the binomial probability distribution to solve this question.
Binomial probability distribution
The binomial probability is the probability of exactly x successes on n repeated trials, and X can only have two outcomes.

In which
is the number of different combinations of x objects from a set of n elements, given by the following formula.

And p is the probability of X happening.
A San Francisco-based tech firm is able to keep 80% of its new employees after one year.
This means that 
Q1. What is the chance that two randomly sampled new employees will both be able to survive their first year
This is P(X = 2) when n = 2. So


0.64 = 64% probability that two randomly sampled new employees will both be able to survive their first year