Ypu would subtract Y from the other points Y
Then you would subtract X from the ither points X.
Then you would put the Y value over the X
Then simiplify
Answer:
-7x + 24
Explanation:
(13x + 30) - (20x + 6)
13x + 30 - 20x - 6
-7x + 30 - 6
-7x + 24
Answer: 1) The best estimate for the average cost of tuition at a 4-year institution starting in 2020 =$ 31524.31
2) The slope of regression line b=937.97 represents the rate of change of average annual cost of tuition at 4-year institutions (y) from 2003 to 2010(x). Here,average annual cost of tuition at 4-year institutions is dependent on school years .
Step-by-step explanation:
1) For the given situation we need to find linear regression equation Y=a+bX for the given situation.
Let x be the number of years starting with 2003 to 2010.
i.e. n=8
and y be the average annual cost of tuition at 4-year institutions from 2003 to 2010.
With reference to table we get
By using above values find a and b for Y=a+bX, where b is the slope of regression line.
and
∴ To find average cost of tuition at a 4-year institution starting in 2020.(as n becomes 18 for year 2020 if starts from 2003 ⇒X=18)
So, Y= 14640.85 + 937.97×18 = 31524.31
∴The best estimate for the average cost of tuition at a 4-year institution starting in 2020 = $31524.31
The percentile rank for 10 will be 10th.
<h3>What is percentile rank?</h3>
The percentile rank of a particular score in statistics refers to the percentage of scores in the frequency distribution that are smaller than that score.
Percentile rank = [(Number of values below x) + 0.5]/ total number of values * 100
For 10,
Percentile rank = {[0 + 0.5]/5} x 100 = 10th
For 15,
Percentile rank = ([1 + 0.5]/5) x 100 = 30st
For 19,
Percentile rank = [2 + 0.5]/5 x 100 = 50th
For 23,
Percentile rank = [3 + 0.5]/5 x 100 = 70th
For 30,
Percentile rank = [4 + 0.5]/ 5 x 100 = 90th
The percentile rank for 10 will be 10th.
To know more about percentile range follow
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Answer:
statement is false
Step-by-step explanation:
given data
men age = 4 year old
relation between = watching television and blood pressure
solution
we can say that this statement is wrong
because here causality it have never implied by correlation between these two watching television time period and the blood pressure as that by watching more time television that not causes high blood pressure
so that statement is false