# ...........................

b) b√a

Step-by-step explanation:

Given equation,

→ ab²

Then the square root of ab² is,

→ square root of ab²

→ √(ab²)

→ b√a

Hence, option (b) is the answer.

B) b√a

Step-by-step explanation:

b√a

## Related Questions

Two points located on jk are j (-1,-9) and k (5,3). What is the slope of jk?

Slope = 2

Step-by-step explanation:

Slope =

Slope =

Slope =

Slope = 2

In the given case, we can conclude that The slope of the line JK is 2.

To find the slope of the line that passes through the points J(-1,-9) and K(5,3), we can use the formula: slope =

The slope of a line is a measure of how steep the line is. It describes the rate at which the dependent variable (usually denoted as 'y') changes with respect to a change in the independent variable (usually denoted as 'x').

Plugging in the coordinates, we get:

slope = (3 - (-9)) / (5 - (-1)) = 12 / 6 = 2.

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Suppose I collected a sample and calculated the sample proportion. If I construct a 90% confidence interval for the population proportion and a 95% confidence interval for the population proportion, which of these intervals will be wider?'

Step-by-step explanation:

If you construct a 90% confidence interval for the population proportion and a 95% confidence interval for the population proportion, the 95% confidence will have a wider interval. This is because a higher confidence interval will provide more possible values from which the true value will be determined. Therefore, If you want more confidence that an interval contains the true parameter, then the intervals will be wider.

Step-by-step explanation:

put a point on -5 and put a point on -4  then write the equation on the top to show what you did, name the points then put a point on -9

x  ≥  1

Step-by-step explanation:

Move all terms not containing x to the right side of the inequality.

−x  ≤  −1

Divide each term in −x ≤ −1  by −1 and simplify.

x  ≥  1

Hope this helps! :)

Population the populations P (in thousands) of Las Vegas Nevada from 1960 through 2009 can be modeled by p = 70.751e 0.0451t, where t is the time in years,with t = 0 corresponding to 1960.(a) Find the populations in 1960,1970,1980,1990,2000,and 2009.
(b) Explain why the change in population from 1960to 1970 is not the same as the change in population from 1980 to 1990.
(c) Use the model to estimate the population in 2020.

Step-by-step explanation:

The model is:

where t is the time in years.

a)

• when t=0 (year 1960)
• when t=10 (year 1970)
• when t=20 (year 1980)
• when t=30 (year 1990)
• when t=40 (year 2000)
• when t=49 (year 2009)

b)

The change in population from 1960to 1970 is 111071-70751 =40320

The change in population from 1980 to 1990 is 273737-174368=99369

The change from 1960to 1970 is not the same as the change from 1980 to 1990 because the model function is not linear, it is exponential. Therefore, the rate of the change is not constant.

c)

The population in 2020 using the model can be estimated as

when t=60 (year 2020)

A researcher wants to determine if the nicotine content of a cigarette is related to​ "tar". A collection of data​ (in milligrams) on 29 cigarettes produced the accompanying​ scatterplot, residuals​ plot, and regression analysis. Complete parts a and b below. ) Explain the meaning of Upper R squared in this context. A. The linear model on tar content accounts for​ 92.4% of the variability in nicotine content. B. The predicted nicotine content is equal to some constant plus​ 92.4% of the tar content. C. Around​ 92.4% of the data points have a residual with magnitude less than the constant coefficient. D. Around​ 92.4% of the data points fit the linear model.

Option A The linear model on tar content accounts for​ 92.4% of the variability in nicotine content.

Step-by-step explanation:

R-square also known as coefficient of determination measures the variability in dependent variable explained by the linear relationship with independent variable.

The given scenario demonstrates that nicotine content is a dependent variable while tar content is an independent variable. So, the given R-square value 92.4% describes that 92.4% of variability in nicotine content is explained by the linear relationship with tar content. We can also write this as "The linear model on tar content accounts for​ 92.4% of the variability in nicotine content".

The Upper R squared or the coefficient of determination here represents the percentage of the variability in the nicotine content that can be explained by the tar content in the regression model, which in this case is 92.4%.

### Explanation:

In this context, the meaning of Upper R squared is represented by option A. The linear model on tar content accounts for 92.4% of the variability in nicotine content. This indicates that 92.4% of the change in nicotine content can be explained by the amount of tar content based on the linear regression model used. This measure is also known as the coefficient of determination. Meanwhile, options B, C, and D are not correct interpretations of the R squared in this context. Both B and D wrongly relate the percentage to the predictability of the data points and option C incorrectly associates this percentage with the residual magnitude.

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Solve the equation for n

y=nx+m

N=?