A license plate consists of a letter, followed by three numbers, followed by another
letter. Due to possible confusion, the letters I and O are not used. Repetition is not
allowed.
How many different license plates are possible?

Decimals start at tenths, then hundredths, then thousandths, and so on. When we round, we look at the place value that is one smaller than the one we want to round to.

So, let's take a look at the thousandths place in 0.485. The value in the thousandths place is 5. When rounding, if the value is 5 or over we round up and if the value is 4 or lower we round down. Since the value in the thousandths place is 5, we will round the hundredths place up one.

0.485 rounded to the nearest hundredth is 0.49

Hope this helps!

Answer:

0.49

Step-by-step explanation:

[tex]0<x<5=[/tex] Round down

[tex]x\geq5=[/tex] Round up

In this case, it's a round up, so the answer would be...

0.49

Hope this helped! Please mark brainliest!

Answer:

The answer is b

Step-by-step explanation:

Step-by-step explanation:

hope it helps you..........

Answer:

cf

=41

5 f-46

Step-by-step explanation:

thiis is the answer

Answer:

To find the inverse, switch the y(F(C)) and the x(C) variables.

So this function:

[tex]y=\frac{9}{5}x+32 \\[/tex]

Will become this function:

[tex]x=\frac{9}{5}y+32 \\[/tex]

You will then solve for y:

[tex]x=\frac{9}{5}y+32 \\x-32=\frac{9}{5}y\\5(x-32)=5(\frac{9}{5}y)\\5x-160=9y\\y=\frac{5x-160}{9}\\y=\frac{5x}{9}-\frac{160}{9}[/tex]

Substitute in the variables of this problem:

[tex]C(F)=\frac{5C}{9}-\frac{160}{9}[/tex]

Answer:

Pvalue = 0.1505

y = 0.550x1 + 3.600x2 + 7.300

Step-by-step explanation:

Given the data :

Study Hours GPA ACT Score

5 4 27

5 2 18

5 3 18

1 3 20

2 4 21

Using technology, the Pvalue obtained using the Fratio :

F = MSregression / MSresidual = 30.228571/ 8.190476 = 3.69

The Pvalue for the regression equation is:

Using the Pvalue from Fratio calculator :

F(1, 3), 3.69 = 0.1505

Using the Pvalue approach :

At α = 0.01

Pvalue > α ; Hence, we fail to reject H0 and conclude that ; There is not enough evidence to show that the relationship is statistically significant.

The regression equation :

y = A1x1 + A2x2 +... AnXn

y = 0.550x1 + 3.600x2 + 7.300

x1 and x2 are the predictor variables ;

y = predicted variable

Answer:

D

Step-by-step explanation:

Answer:

[tex]\frac{-2x+11}{(x-4)(x+1)}[/tex]

Step-by-step explanation:

I don't think we can factor this so we'll have to multiply to make the denominators the same

[tex]\frac{3(x+1)}{(x^2-3x-4)(x+1)}-\frac{2(x^2-3x-4)}{(x+1)(x^2-3x-4)}\\\\\frac{3x+3-(2x^2-6x-8)}{(x^2-3x-4)(x+1)}=\frac{-2x^2+9x+11}{(x^2-3x-4)(x+1)}\\-2x^2+9x+11=(x+1)(-2x+11)\\\\x^2-3x-4=(x+1)(x-4)\\\frac{(x+1)(-2x+11)}{(x+1)(x-4)(x+1)}=\frac{-2x+11}{(x-4)(x+1)}[/tex]

Answer:

There may be 1 or 3 tricycles in the parking lot.

Step-by-step explanation:

Since at any point in time, there could be bicycles, tricycles, and cars in the school parking lot, and today, there are 53 wheels in total, if there are 15 bicycles, tricycles, and cars in total, to determine how many tricycles could be in the parking lot, the following calculation must be performed:

13 x 4 + 1 x 3 + 1 x 2 = 57

11 x 4 + 1 x 3 + 3 x 2 = 53

10 x 4 + 3 x 3 + 2 x 2 = 53

8 x 4 + 5 x 3 + 2 x 2 = 51

10 x 2 + 1 x 3 + 4 x 4 = 39

9 x 3 + 1 x 2 + 5 x 4 = 49

Therefore, there may be 1 or 3 tricycles in the parking lot.

Answer:

The level of significance is the

b. maximum allowable probability of Type I error.

Step-by-step explanation:

The significance level provides the maximum probability of rejecting the null hypothesis when it is true.  It is the same as a type I error (also known as false-positive).  This error occurs when a researcher or investigator rejects a true null hypothesis that is supposed to be accepted.  It is the opposite of a type II error (false-negative), which occurs when the researcher fails to reject a false null hypothesis.

compute is an electronic devices

Answer:

hlo how are u?whats ur day is going

Answer: hi your question is poorly written below is the correct question

answer :

a) y1 = Asint,   y'1 = Acost  , y"1 = -Asint

b) y2 = Bcost,   y'2 = Bsint , y"2 = - Bcost

c) y = Asint + B cost satisfies the differential equation for any constant A and B

Step-by-step explanation:

y" + y = 0

Proves

a) y1 = Asint,   y'1 = Acost  , y"1 = -Asint

b) y2 = Bcost,   y'2 = Bsint , y"2 = - Bcost

c) y3 = y1 + y2 ,   y'3 = y'1 + y'2,  y"3 = y"1 + y"2

∴ y"1 + y1 = -Asint + Asint

  y"2 + y2 = -Bcost + Bcost

  y"3 - y3 = y"1 + y"2 - ( y1 + y2 )

               = y"1 - y1 + y"2 - y2  

               = -Asint - Asint  + ( - Bcost - Bcost )  = 0

Hence we can conclude that y = Asint + B cost satisfies the equation for any constant A and B

Answer:

[tex]Z=-2.87[/tex]

Step-by-step explanation:

From the question we are told that:

Probability on women

[tex]P(W)=65 / 500[/tex]

[tex]P(W) = 0.13[/tex]

Probability on women

[tex]P(M)=133 / 700[/tex]

[tex]P(M) = 0.19[/tex]

Confidence Interval [tex]CI=99\%[/tex]

Generally the equation for momentum is mathematically given by

[tex]Z = \frac{( P(W) - P(M) )}{\sqrt{(\frac{ \sigma_1 * \sigma_2 }{(1/n1 + 1/n2)}}})[/tex]

Where

[tex]\sigma_1=(x_1+x_2)(n_1+n_2)[/tex]

[tex]\sigma_1=\frac{( 65 + 133 )}{ ( 500 + 700 )}[/tex]

[tex]\sigma_1=0.165[/tex]

And

[tex]\sigma_2=1 - \sigma = 0.835[/tex]

Therefore

[tex]Z = \frac{( 0.13 - 0.19)}{\sqrt{\frac{( 0.165 * 0.835}{ (500 + 700) )}}}[/tex]

[tex]Z=-2.87[/tex]

9514 1404 393

Answer:

  x = 7

Step-by-step explanation:

Vertical angles have the same measure, so ...

  m∠A = m∠B

  (5x -9)° = (8x -30)°

  21 = 3x . . . . . . . . . divide by °, add 30-5x

  7 = x . . . . . . . . . . divide by 3

Answer:

A=W, B=X, C=Y, D=Z, AB=WX, BC=XY, CD=YZ, AD=WZ

(The second answer down)

Step-by-step explanation:

Answer:

71, 71, 75, 85, 98, 98, 104, 111, 114, 122, 164

The middle quartile is 98.

The lower quartile is 80

The upper quartile is 112.5

Answer:

FALSE

Step-by-step explanation:

The regression equation is a prediction model which is generated for a given independent, x and dependent, y variable. The regression model is usually ideal when both the dependent and independent variables are numerical. The regression equation cannot be generated if either the x or y value is non-numeric. In such situation, classification models may be better suited for such cases especially if there is no efficient method of converting the non-numeric column into a numeric variable.

Step-by-step explanation:

ejejejejrjruruehehhr

Answer:

[tex]P = 8 + 2\sqrt{26}[/tex]

Step-by-step explanation:

Given

[tex]W = (-2, 4)[/tex]

[tex]X = (2, 4)[/tex]

[tex]Y = (1, -1)[/tex]

[tex]Z = (-3,-1)[/tex]

Required

The perimeter

First, calculate the distance between each point using:

[tex]d = \sqrt{(x_1 - x_2)^2 + (y_1 -y_2)^2[/tex]

So, we have:

[tex]WX = \sqrt{(-2- 2)^2 + (4-4)^2 } =4[/tex]

[tex]XY = \sqrt{(2- 1)^2 + (4--1)^2 } =\sqrt{26}[/tex]

[tex]YZ = \sqrt{(1- -3)^2 + (-1--1)^2 } =4[/tex]

[tex]ZW = \sqrt{(-3--2)^2 + (-1-4)^2 } =\sqrt{26}[/tex]

So, the perimeter (P) is:

[tex]P = 4 + \sqrt{26} + 4 + \sqrt{26}[/tex]

[tex]P = 8 + 2\sqrt{26}[/tex]

Answer:

its D.

Step-by-step explanation:

took test

Answer:

[tex]{ \bf{c). \: g(x) = {2}^{x} - 2 }}[/tex]

Answer:

[tex]\frac{23x-37}{x-4}[/tex]

Step-by-step explanation:

Answer:

C

Step-by-step explanation:

Start by simplifying what you can in each radicalfor example, the

∛(xy⁵)= y∛(xy²)

and

∛(x⁷y¹⁷)=x²y⁵∛(xy²)

So know our equation looks like

y∛(xy²)*x²y⁵∛(xy²)

Now because what's inside the radical is the same we can combine them

y⁶x²∛(xy²)²

distribute the square

so

∛(xy²)²=  ∛(x²y⁴)= y∛(x²y)

and finally,

y⁶x²*y∛(x²y)= y⁷x²∛(x²y)

this is equal to option C

Answer:

1 2/7 ........................................

Answer:

1 2/7.

Step-by-step explanation:

Divide 9 by 7 :- this gives 1 with a remainder of 2.

So it is 1 2/7.

Total outcomes=6 i.e{1,2,3,4,5,6 }

No.of favourable outcomes = 3 i.e {I, 3,5}

P(odd)=3/6=1/2

Answer:

1/ 2

Step-by-step explanation:

[tex]probability \: of \:an \:event\: = \frac{number \: of \: favorable outcomes}{total \: number \: of \: outcomes} [/tex]

favorable outcomes = odd numbers

=1, 3, 5

number of favorable outcomes = 3

total outcomes

= 1, 2, 3, 4, 5, 6

total number of outcomes = 6

probability = 3/ 6

= 1/ 2

Answer:

0.0098 = 0.98% probability that the sample proportion will differ from the population proportion by greater than 0.04

Step-by-step explanation:

To solve this question, we need to understand the normal probability distribution and the central limit theorem.

Normal Probability Distribution:

Problems of normal distributions can be solved using the z-score formula.

In a set with mean [tex]\mu[/tex] and standard deviation [tex]\sigma[/tex], the z-score of a measure X is given by:

[tex]Z = \frac{X - \mu}{\sigma}[/tex]

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the p-value, we get the probability that the value of the measure is greater than X.

Central Limit Theorem

The Central Limit Theorem establishes that, for a normally distributed random variable X, with mean [tex]\mu[/tex] and standard deviation [tex]\sigma[/tex], the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean [tex]\mu[/tex] and standard deviation [tex]s = \frac{\sigma}{\sqrt{n}}[/tex].

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

For a proportion p in a sample of size n, the sampling distribution of the sample proportion will be approximately normal with mean [tex]\mu = p[/tex] and standard deviation [tex]s = \sqrt{\frac{p(1-p)}{n}}[/tex]

Suppose the true proportion is 0.06.

This means that [tex]p = 0.06[/tex]

235 are sampled

This means that [tex]n = 235[/tex]

Mean and standard deviation:

[tex]\mu = p = 0.06[/tex]

[tex]s = \sqrt{\frac{p(1-p)}{n}} = \sqrt{\frac{0.06*0.94}{235}} = 0.0155[/tex]

What is the probability that the sample proportion will differ from the population proportion by greater than 0.04?

Proportion below 0.06 - 0.04 = 0.02 or above 0.06 + 0.04 = 0.1. Since the normal distribution is symmetric, these probabilities are equal, which means that we can find one of them and multiply by 2.

Probability the proportion is below 0.02.

p-value of Z when X = 0.02. So

[tex]Z = \frac{X - \mu}{\sigma}[/tex]

By the Central Limit Theorem

[tex]Z = \frac{X - \mu}{s}[/tex]

[tex]Z = \frac{0.02 - 0.06}{0.0155}[/tex]

[tex]Z = -2.58[/tex]

[tex]Z = -2.58[/tex] has a p-value of 0.0049.

2*0.0049 = 0.0098

0.0098 = 0.98% probability that the sample proportion will differ from the population proportion by greater than 0.04

The sample statistic that must have changed after the correction was made is mean. Because mean is based on all the observation in the data. So changing any value in the data will impact mean.

Changing the highest salary in the data will have no impact on median because median lies at the center of data.

Changing the highest salary in the data will have no impact on mode because mode is the most frequently occurring value in the data.

Changing the highest salary in the data will have no impact on minimum because minimum is the smallest value in the data.

Hence the only statistic which will change is mean.

Answer: A-Mean

Step-by-step explanation:

A.) Mean

B.) Median

C.)  Mode

D.)  Minimum

Answer:

$7.13

Step-by-step explanation:

Given data

Cost of halibut per pound= $19

Let us convert pound to ounces first

1 pound = 16 ounces

Hence 16 ounces will cost $19

           6 ounces will cost x

cross multiply we have

x= 19*6/16

x=114/16

x=$7.13

Hence 6 ounces will cost $7.13

Answer:

The alternative hypothesis is [tex]H_1: \mu_M - \mu_W \neq 0[/tex], considering M for men and W for women.

Step-by-step explanation:

He uses the data to conduct a hypothesis test to determine if the mean percent of expenditures that goes toward housing (including fuel and light) is different for men and women.

At the null hypothesis, we test if there is not difference, that is, the difference of the mean is 0, so:

[tex]H_0: \mu_M - \mu_W = 0[/tex]

At the alternative hypothesis, we test if there is a difference, that is, the difference of the means is different of 0, so:

[tex]H_1: \mu_M - \mu_W \neq 0[/tex]

Step-by-step explanation:

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