The XO Group Inc. conducted a survey of 13,000 brides and grooms married in the United States and found that the average cost of
1 answer:
Answer:
0.0392,0.4709, 38083
Step-by-step explanation:
Given that XO Group Inc. conducted a survey of 13,000 brides and grooms married in the United States and found that the average cost of a wedding is $29,858
X is N(29,858, 5600)
Or is N*(0,1)
We can use std normal distribution table to get the probabilities
a) The probability that a wedding costs less than $20,000 (to 4 decimals)
=
=0.0392
b) the probability that a wedding costs between $20,000 and $30,000
=
c) For a wedding to be among the 5% most expensive, how much would it have to cost (to the nearest whole number)
=
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Answer:
1,496 new car buyers
Step-by-step explanation:
The sample size n in Simple Random Sampling is given by
where
z = 1.645 is the critical value for a 90% confidence level (*)
p= 0.33 is the population proportion.
e = 0.02 is the margin of error
so
<em>(*)</em><em>This is a point z such that the area under the Normal curve N(0,1) inside the interval [-z, z] equals 90% = 0.9</em>
It can be obtained in Excel or OpenOffice Calc with
<em>NORMSINV(0.95)</em>
Answer:
A circle can intersect a parabola in
1. One point [ when circle just touches the parabola]
2. Two points [ When circle cuts the parabola in two distinct points. ]
3. Three points [Circle just touches at one point and cuts the parabola in two distinct points]
4. Four points [ Either parabola or circle meeting each other or crossing at four distinct points]
Answer:
- Keisha’s experimental probability is 1/50.
- When the inventory is 4000 clocks, the prediction is that 3920 clocks will work.
- Keisha will have more than 97% of the products working.
Step-by-step explanation:
These are three prediction that Keisha can make based on the report that said 6 of 300 clocks tested weren't working.
Base on that information, Keisha can calculate an experimental probability, dividing <em>clocks that don't work properly </em>by <em>the total amount of clocks</em><em>:</em>
<em></em>
Therefore, the probability of success is 100% - 2% = 98%.
This means that Keisha has a probability of having 98% of all clocks functioning properly. So, she can make the prediction:<em> from 4000 clocks, 3920 will work. </em>Also, she can predict that she will actually have more than 97% working, because the experimental probability is higher than that.