A rectangle is enlarged by a factor of 6.<br> What is the area of the enlarged rectangle.

Consider all seven-digit numbers that can be created from the digits 0-9 where the first and last digits must be odd and no digi

Yuliya22 [10]

Answer:

1/4 or 0.25

Step-by-step explanation:

The total possibilities of any 7 digit number using 0-9 is :

9×10×10×10×10×10×10=9000000

To work out the total possibilities in this question :

We look at the conditions :

The first digit can only be 5 numbers :

1 , 3 , 5 , 7 , 9

Now we subtract 5 from 9 :

9-5 = 4

Since no repeats for 2 , 3 , 4, 5, 6:

9 , 8 , 7 , 6 , 5,

5 possibilities for the last digit :

Total possibilities for this code :

4 × 9 × 8 × 7 × 6 × 5 × 5 = 302400

If it begins with 5 that is only 1 possibility for the first digit

1 × 9 × 8 × 7 × 6 × 5 × 5 = 75600

Now we make a fraction :

75600÷302400

Dividing top and bottom by 75600 gives you 1/4 or 0.25

Hope this helped and have a good day

7 0

2 years ago

Read 2 more answers

When you write a numerical expression how can you show which operation to do it first?

kenny6666 [7]

Answer:

parentheses come first

Step-by-step explanation:

Parentheses are symbols that group things together. This becomes very important in numerical expressions, because operations inside parentheses are always completed first when evaluating the expression. Let's review the order of operations. You can see that, according to the order of operations, parentheses come first.

7 0

3 years ago

An interior automotive supplier places several electrical wires in a harness.Apull test measures the force required to pull spli

oksano4ka [1.4K]

Answer:

a) For this case we can use the following R code to construct the qq plot

> data<-c(28.8, 24.4, 30.1, 25.6, 26.4, 23.9, 22.1, 22.5, 27.6, 28.1, 20.8, 27.7, 24.4, 25.1, 24.6, 26.3, 28.2, 22.2, 26.3, 24.4)

# The above line is in order to store the data in a vector

> qqnorm(data, pch = 1, frame = FALSE)

# The line above is in order to calculate the quantiles from the data assumin Normal distribution

> qqline(data, col = "steelblue", lwd = 2)

# The line above is in order to put a line for the theoretical dsitribution

The result is on the figure attached.

b) For this case as we can see on the figure attached the calculated quantiles are not far from the theorical quantiles given byt the straaigth blue line so then we can conclude that the distribution seems to be normal.

Step-by-step explanation:

For this case we have the following data:

28.8, 24.4, 30.1, 25.6, 26.4, 23.9, 22.1, 22.5, 27.6, 28.1, 20.8, 27.7, 24.4, 25.1, 24.6, 26.3, 28.2, 22.2, 26.3, 24.4

The quantile-quantile or q-q plot is a graphical procedure in order to check the validity of a distributional assumption for a data set. We just need to calculate "the theoretically expected value for each data point based on the distribution in question".

If the values are asusted to the assumed distribution, we will see that "the points on the q-q plot will fall approximately on a straight line"

For this case our distribution assumed is normal.

Part a

For this case we can use the following R code to construct the qq plot

> data<-c(28.8, 24.4, 30.1, 25.6, 26.4, 23.9, 22.1, 22.5, 27.6, 28.1, 20.8, 27.7, 24.4, 25.1, 24.6, 26.3, 28.2, 22.2, 26.3, 24.4)

# The above line is in order to store the data in a vector

> qqnorm(data, pch = 1, frame = FALSE)

# The line above is in order to calculate the quantiles from the data assuming Normal distribution (0,1)

> qqline(data, col = "steelblue", lwd = 2)

# The line above is in order to put a line for the theoretical distribution

The result is on the figure attached.

Part b

For this case as we can see on the figure attached the calculated quantiles are not far from the theorical quantiles given byt the straaigth blue line so then we can conclude that the distribution seems to be normal.