Answer:
$0 < p ≤ $25
Step-by-step explanation:
We know that coach Rivas can spend up to $750 on 30 swimsuits.
This means that the maximum cost that the coach can afford to pay is $750, then if the cost for the 30 swimsuits is C, we have the inequality:
C ≤ $750
Now, if each swimsuit costs p, then 30 of them costs 30 times p, then the cost of the swimsuits is:
C = 30*p
Then we have the inequality:
30*p ≤ $750.
To find the possible values of p, we just need to isolate p in one side of the inequality.
So we can divide both sides by 30 to get:
(30*p)/30 ≤ $750/30
p ≤ $25
And we also should add the restriction:
$0 < p ≤ $25
Because a swimsuit can not cost 0 dollars or less than that.
Then the inequality that represents the possible values of p is:
$0 < p ≤ $25
Answer:
P=648
Step-by-step explanation:
Answer:
The score that cuts off the bottom 2.5% is 48.93.
Step-by-step explanation:
When the distribution is normal, we use the z-score formula.
In a set with mean 
and standard deviation 
, the zscore of a measure X is given by:
The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.
In this question, we have that:
What is the score that cuts off the bottom 2.5%
This is X when Z has a pvalue of 0.025, so X when Z = -1.96.
The score that cuts off the bottom 2.5% is 48.93.
Answer:
True.
Step-by-step explanation:
A probability distribution is a listing of all the outcomes of an experiment and the probability associated with each outcome. Probability distribution is associated with the following characteristics or properties;
1. The outcomes are mutually exclusive.
2. The list of outcomes is exhaustive, which simply means that the sum of all probabilities of the outcomes must equal one (1).
3. The probability for a particular value or outcome must be between 0 and 1.
Since a probability distribution gives the likelihood of an outcome or event, a single random variable is divided into two main categories, namely;
I. Probability density functions for continuous variables.
II. Discrete probability distributions for discrete variables.
For example, when a coin is tossed, you can only have a head or tail (H or T).
Also, when you throw a die, the only possible outcome is 1/6 and the total probability for it all must equal to one (1).
Answer:
Micky woke up at 7:30 p.m
Step-by-step explanation:
Hope it helped! please mark brainliest!
