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skad [1K]
2 years ago
7

A store sells 20 ice cream bars per hour for $4 each, but on discount days, it sells 35 ice cream bars per hour for $3. Based on

these two data points, what would be the slope for the relationship between the price and the quantity of ice cream sold? (price is on the vertical axis).
SAT
1 answer:
strojnjashka [21]2 years ago
7 0

The slope for the relationship between the price and the quantity of ice cream sold is -$0.067 per unit

<h3>Linear equation</h3>

A linear equation is in the form:

y = mx + b

where y, x are variables, m is the rate of change and b is the y intercept.

Let y represent the price (vertical axis) and x represent the quantity.

The slope = ($3 - $4)/(35 - 20) = -$0.067 per unit

The slope for the relationship between the price and the quantity of ice cream sold is -$0.067 per unit

Find out more on linear equation at: brainly.com/question/14323743

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<h3>Answers: Choice B and Choice C</h3>

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Explanation:

The symbol \mu or mu represents the population mean, which is a parameter.

The symbol \sigma or sigma represents the population standard deviation, which is also a parameter. The same goes for the symbol p, without any hat on top, as it is the population proportion.

If something represents a population data item, then it's automatically a parameter. It might help to think both words "population" and "parameter" start with the letter P.

Based on those previous paragraphs, we can rule out choices A, D and E. Those three items are parameters. This leaves <u>choices B and C</u> as our final answers.

\overline{x} or xbar is a sample statistic, and it represents an estimate of the population mean. Similarly, \hat{p} or p-hat is the sample proportion and it represents an estimate of the population proportion. These are considered unbiased estimators.

Another example of an unbiased estimator is the variable s which represents the sample standard deviation and it estimates the value of sigma. All of these estimators have one thing in common: they are based on a sample, which in turn tries to predict what the corresponding population value is. In other words, the statistic's job is to estimate the parameter.

Below is a reference table for all of the items mentioned.

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The complete question is:

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