The linear model is the best fit for the relationship.
According to the statement
we have given that the relationship between gross box office sales and home video units significant and the linear model is the best fit for the relationship.
And we explain all the given statements.
So, For this purpose, we know that the
Since the p-value of the independent variable, 0.0000, is less than 0.05, we can be 95% confident that there is a significant linear relationship between gross box office and home video units.
And the
linear model is used in different ways according to the context. The most common occurrence is in connection with regression models.
So, the linear model is appropriate for the comparisons.
So, The linear model is the best fit for the relationship.
Learn more about linear model here
brainly.com/question/4025726
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The median is the middle number, the range is the difference between the lowest and highest values(subtract the lowest number from the highest number) and the mode is the number that appears most often in a set of numbers
Hope this helps
Answer:
Step-by-step explanation:
wht grade are you on
Answer:
x = 64 m
Step-by-step explanation:
The scale is proportional to the actual:
(6 m)/(3/4 cm) = x/(8 cm)
Multiplying by 8 cm, we get ...
x = (8 cm)·(6 m)/(3/4 cm)
x = 64 m . . . . the width of the actual wall
The probability that it also rained that day is to be considered as the 0.30 and the same is to be considered.
<h3>
What is probability?</h3>
The extent to which an event is likely to occur, measured by the ratio of the favorable cases to the whole number of cases possible.
The probability that the temperature is lower than 80°F and it rained can be measured by determining the number at the intersection of a temperature that less than 80°F and rain.
So, This number is 0.30.
Hence, we can say that it was less than 80°F on a given day, the probability that it also rained that day is 0.30.
To learn more about the probability from the given link:
brainly.com/question/18638636
The above question is incomplete.
The conditional relative frequency table was generated using data that compared the outside temperature each day to whether it rained that day. A 4-column table with 3 rows titled weather. The first column has no label with entries 80 degrees F, less than 80 degrees F, total. The second column is labeled rain with entries 0.35, 0.3, nearly equal to 0.33. The third column is labeled no rain with entries 0.65, 0.7, nearly equal to 0.67. The fourth column is labeled total with entries 1.0, 1.0, 1.0. Given that it was less than 80 degrees F on a given day, what is the probability that it also rained that day?
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