You are correct for 18a through 18c. Nice work.
18a. True (think of it as 21 is less than 27)
18b. False; 0.4 is the same as 0.40
18c. True. Three dollars is much greater than 20 cents
18d. False. 1.9 is the same as 1.90 and can't be smaller than itself
18e. False. The two sides are completely diferrent numbers.
18f. True. The value 6.2 is the same as 6.20
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For problem 19, you have to make the denominators the same. So multiply top and bottom of the first fraction by 10 to go from 4/10 to 40/100
If 40 is in the first box, then 40+40 = 80 is the final numerator. If this is over 100, then 80/100 = 8/10 meaning that 10 goes in the other box.
Answer:
B
Step-by-step explanation:
Follow the arrow from the x- value in the domain to the corresponding value in the range, that is
x = - 1 → f(- 1) = 5
x = 0 → f(0) = 3
x = 1 → f(1) = 5
x = 2 → f(2) = 11
x = 3 → f(3) = 21
Thus B shows the appropriate mapping
I used arm span as the x-axis and height as the y-axis; arm span is the independent variable because height is typically dependent on arm span. Although the opposite could be argued for.
The equation of the line of best fit is y= 12+(7/9)x. To get the slope I used the points (37,39) and (19,25). The slope is therefore 14/18=7/9. The slope represents that height increases by 7/9 inches when arm span increases by 1 inch. The y-intercept 12 represents roughly the height when arm size is very small. I tested the residuals of the points (47,49) and (58,61). The respective predictions are 48.556 and 57.111. The respective residuals are then (49-48.556)=0.444 and (61-57.111)=3.889. It seems that the line models the data well until the x values get larger, where the performance decreases. The line of best fit with its positive slope indicates that there is a positive correlation with arm span and height.
Using the model, a person with arm span 66 inches has a height of 12+(7/9)*66= 63.333 inches. A person with 74 inches height has an estimated arm span of 62*9/7= 79.714 inches.