What is 1.64 million rounded to the nearest million

Answers

Answer 1

Answer: 1.64 million rounded to the nearest million is 2 million.

Answer 2

Answer: 2 million. Rememer. If you are rounding, if its 5 or more up the score, for or less let it rest.

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Can you help! What is 48771273 + 68296638918

Answers

The correct answer is :

68,345,410,191.

48,771,273 + 68,296,638,918 = 68,345,410,191.

Hope this helps,

Davinia :)

Why didn’t you use a calculator?

How many millimeters in one centimeter

Answers

There are exactly 10 millimeters in one centimeter

There is 1 mili in one centimeter

Is y=7.5x a proportional relationship and why

Answers

Direct Proportion functions look like this:

y=kx

'k' is the constant of proportionality and in this case its 7.5 or 15/2.

--------------------------------------------

When x=1, y=7.5
When x=2, y=15
When x=3, y=22.5

Therefore y is directly proportional to x.

--------------------------------------

DIRECT PROPORTION EXPLAINED:

Say a football costs £7.50. If you buy one football you'll have to pay out £7.50, but if you you buy two footballs you'll have to pay out £15.00. Therefore the cost of the football(s) is directly proportional to the amount of footballs you buy. C=cost, f=football(s) and C∝f, therefore C=kf, but as k=7.5, C=7.5f.

INVERSE PROPORTION EXPLAINED:

If it were to take 8 hours for one bricklayer to set up a wall, how long would it take for two bricklayers to set up a wall? The answer in this case would be 4 hours.

T=time to set up a wall
b=bricklayer(s)

Therefore T∝1/b, and T=k/b. In this case k=8 so T=8/b.

When b=1, T=8.
When b=2, T=4.

We'd say that the time it would take for bricklayers to set up a wall would be inversely proportional to the amount of bricklayers available.

(4x ^2+2x+1) (x^2-3x+5)

Answers

Answer:

You need to multiply the polynomials. Please see attached picture for answer.

= 4x ^4 + -10x^3 + 15x^2 + 7x +5

Step-by-step explanation:

You need to multiply each term step by step

(4x ^2+2x+1)*(x^2) + (4x ^2+2x+1)*(-3x) + (4x ^2+2x+1)*5

= (4x ^4 + 2x^3 +x^2) + (-12x ^3 - 6x^2 -3x) + (20x ^2+10x+5)

= 4x ^4 + -10x^3 + 15x^2 + 7x +5

What is 6.245 rounded to the nearest hundredth?

Answers

6.25. Because the 5 makes the 4 round up to the next digit which is 5

6.25 anything at or above five rounds up the other number.

Arm Span(x) Height(y) (58, 60)
(49, 47)
(51, 55)
(19, 25)
(37, 39)
(44, 45)
(47, 49)
(36, 35)
(41, 40)
(46, 50)
(58, 61)
(67, 63)

1. Representation of Data with Plots Using graphing software of your choice, create a scatter plot of your data. Predict the line of best fit, and sketch it on your graph. Copy and paste your scatter plot into a word processing document.

2. The Line of Best Fit Include your scatter plot and the answers to the following questions in your word processing document:

Which variable did you plot on the x-axis, and which variable did you plot on the y-axis? Explain why you assigned the variables in that way.

Write the equation of the line of best fit using the slope-intercept formula y = mx + b. Show all your work, including the points used to determine the slope and how the equation was determined.

What does the slope of the line represent within the context of your graph? What does the y-intercept represent?

Test the residuals of two other points to determine how well the line of best fit models the data. Use the line of best fit to help you to describe the data correlation.

Using the line of best fit that you found in 2, approximate how tall is a person whose arm span is 66 inches?

According to your line of best fit, what is the arm span of a 74-inch-tall person?

Answers

Answer:

Here's what I get.

Step-by-step explanation:

1. Representation of data

I used Excel to create a scatterplot of the data, draw the line of best fit, and print the regression equation.

2. Line of best fit

(a) Variables

I chose arm span as the dependent variable (y-axis) and height as the independent variable (x-axis).

It seems to me that arm span depends on your height rather than the other way around.

(b) Regression equation

The calculation is easy but tedious, so I asked Excel to do it.

For the equation y = ax + b, the formulas are

$a = (\sum y \sum x^(2) - \sum x \sumxy)/(n\sum x^(2)- \left (\sum x\right )^(2))\n\nb = (n\sumx y - \sum x \sumxy)/(n\sum x^(2)- \left (\sum x\right )^(2))$

This gave the regression equation:

y = 1.0595x - 4.1524

(c) Interpretation

The line shows how arm span depends on height.

The slope of the line says that arm span increases about 6 % faster than height.

The y-intercept is -4. If your height is zero, your arm length is -4 in (both are impossible).

(d) Residuals

$\begin{array}{cccr}&\textbf{Arm Span} & \textbf{Arm Span}&\n\textbf{Height/in} &\textbf{Actual} & \textbf{Predicted}&\textbf{Residual}\n25 & 19 & 22.3 & -3.3\n40 & 41 & 38.2 & 2.8\n55 & 51 & 54.1 & -3.1\n65 & 67 & 62.6 & 4.4\n \end{array}$

The residuals appear to be evenly distributed above and below the predicted values.

A graph of all the residuals confirms this observation.

The equation usually predicts arm span to within 4 in.

(e) Predictions

(i) Height of person with 66 in arm span

$\begin{array}{rcl}y& = & 1.0595x - 4.1524\n66 & = & 1.0595x - 4.1524\n70.1524 & = & 1.0595x\nx & = & (70.1524)/(1.0595)\n\n& = & \textbf{66 in}\n\end{array}\n\text{A person with an arm span of 66 in should have a height of about $\large \boxed{\textbf{66 in}}$}$

(ii) Arm span of 74 in tall person

$\begin{array}{rcl}y& = & 1.0595x - 4.1524\n& = & 1.0595*74 - 4.1524\n& = & 78.4030 - 4.1524\n& = & \textbf{74 in}\n\end{array}\n\text{ A person who is 74 in tall should have an arm span of $\large \boxed{\textbf{74 in}}$}$

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