Answer:
See explanation
Step-by-step explanation:
Solution:-
- The researcher claims :
" the average annual salary of part-time community college instructors is at least $45,000 "
- We will extract the claim made by the researcher to be the Null hypothesis:
Null Hypothesis : μ ≥ $45,000
- Any statement otherwise, or point of rejection criteria will denote the Alternate hypothesis that disbands the claim that:
" the average annual salary of part-time community college instructors is less than $45,000 " :
Alternate Hypothesis : μ < $45,000
- This type of test with a sample size of n = 25 < 30 and population standard deviation is also not given hints the use t-test statistics and t-critical value reject the claim.
Lower tail - one sample - T-test.
Find the number that both can be divided by i.e. the common denominator of 56/8 is 8 because 56 is divisible by 8 and 8 is also divisible by 8.
so by finding the common denominator and dividing the fraction, the equation would look like this: 7/1
<h3>
Answer: 19 dimes</h3>
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Work Shown:
d = number of dimes
q = 32-d = number of quarters
$5.15 = 515 cents
10d+25q = 515
10d+25(32-d) = 515
10d+800-25d = 515
-15d+800 = 515
-15d = 515-800
-15d = -285
d = -285/(-15)
d = 19
There are 19 dimes. You can stop here if you want.
q = 32-d = 32-19 = 13
There are 13 quarters
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Check:
1 dime = 10 cents
19 dimes = 19*10 = 190 cents
1 quarter = 25 cents
13 quarters = 13*25 = 325 cents
total value = 190 cents + 325 cents = 515 cents = $5.15
The answer is confirmed.
Answer:
The correct options are: Interquartile ranges are not significantly impacted by outliers. Lower and upper quartiles are needed to find the interquartile range. The data values should be listed in order before trying to find the interquartile range. The option Subtract the lowest and highest values to find the interquartile range is incorrect because the difference between lowest and highest values will give us range. The option A small interquartile range means the data is spread far away from the median is incorrect because a small interquartile means data is nor spread far away from the median
