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3 years ago

If x = 3 and f(x) = 45 what is the linear equation

Mathematics

1 answer:

faust18 [17]3 years ago

8 0

Answer:

Step-by-step explanation:

x=3 f(x)=45

45/3=f

f=15

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Suppose that each semester at a particular community college Manuel has to pay $1478 in tuition and $121 in fees.

Kamila [148]

Answer:

Step-by-step explanation:

Let x be time, in semesters, remaining before Manuel graduates. We find that Manuel's expenses are:

$1478/semester in tuition, and

$121/semester in fees

1. x semesters remaining: fees

Remaining cost for fees, y, is the product of the fee times the number of semesters, x:

y =($121/semester)*x

y = ($121)*x

2. x semesters remaining: tuition

Remaining cost, y, is the product of the tuition (times the number of semesters, x.

y = ($1478/semester)*x + ($121/semester)*x

y = ($1599)*x

3. x semesters remaining: tuition and fees

Remaining cost, y, is the sum of the products of the tuition (times the number of semesters, and the fees (tix.

y = ($1478/semester)*x + ($121/semester)*x

y = ($1599)*x

5 0

1 year ago

So I have these two assignments and their due in today and 12:00 so if anybody can please give me the answers real quick it woul

LUCKY_DIMON [66]

Answer:

77°, 103°

Step-by-step explanation:

x=103°

z=x=103°
y=180°-x=180°-103°=77°

-----------

∠5= 42°

∠3= 180°-42°=138°

4 0

3 years ago

1. The probability of telesales representative making a sale on a customer call is 0.15.

Mumz [18]

Answer:

$n = 33$

$n = 19$

Step-by-step explanation:

From the question we are told that

The probability of telesales representative making a sale on a customer call is $p = 0.15$

The mean is $\mu = 5$

Generally the distribution of sales call made by a telesales representative follows a binomial distribution

i.e

$X \~ \ \ \ B(n , p)$

and the probability distribution function for binomial distribution is

$P(X = x) = ^{n}C_x * p^x * (1- p)^{n-x}$

Here C stands for combination hence we are going to be making use of the combination function in our calculators

Generally the mean is mathematically represented as

$\mu = n* p$

=> $5= n * 0.15$

=> $n = 33$

Generally the least number of calls that need to be made by a representative for the probability of at least 1 sale to exceed 0.95 is mathematically represented as

$P( X \ge 1) = 1 - P( X < 1 ) > 0.95$

=> $P( X \ge 1) = 1 - P( X =0 ) > 0.95$

=> $P( X \ge 1) = 1 - [ ^{n}C_0 * (0.15 )^0 * (1- 0.15)^{n-0}] > 0.95$

=> $1 - [1 * 1* (0.85)^{n}] > 0.95$

=> $[(0.85)^{n}] > 0.05$

taking natural log of both sides

$n = \frac{ln(0.05)}{ln(0.85)}$

=> $n = 19$

3 0

2 years ago

And example of commutative property of multiplication

FromTheMoon [43]

Answer:

4 × 3 = 3 × 4 4 \times 3 = 3 \times 4 4×3=3×44, times, 3, equals, 3, times, 4.

8 0

2 years ago

Read 2 more answers

To test whether or not there is a difference between treatments A, B, and C, a sample of 12 observations has been randomly assig

Keith_Richards [23]

Answer:

1. Null hypothesis: $\mu_{A}=\mu_{B}=\mu_{C}$

Alternative hypothesis: Not all the means are equal $\mu_{i}\neq \mu_{j}, i,j=A,B,C$

2. D. 36

3. C. 34

4. B. 1.059

5. B. 8.02

Step-by-step explanation:

Analysis of variance (ANOVA) "is used to analyze the differences among group means in a sample".

The sum of squares "is the sum of the square of variation, where variation is defined as the spread between each individual value and the grand mean"

Part 1

The hypothesis for this case are:

Null hypothesis: $\mu_{A}=\mu_{B}=\mu_{C}$

Alternative hypothesis: Not all the means are equal $\mu_{i}\neq \mu_{j}, i,j=A,B,C$

Part 2

In order to find the mean square between treatments (MSTR), we need to find first the sum of squares and the degrees of freedom.

If we assume that we have $p$ groups and on each group from $j=1,\dots,p$ we have $n_j$ individuals on each group we can define the following formulas of variation:

$SS_{total}=\sum_{j=1}^p \sum_{i=1}^{n_j} (x_{ij}-\bar x)^2$

$SS_{between}=SS_{model}=\sum_{j=1}^p n_j (\bar x_{j}-\bar x)^2$

$SS_{within}=SS_{error}=\sum_{j=1}^p \sum_{i=1}^{n_j} (x_{ij}-\bar x_j)^2$

And we have this property

$SST=SS_{between}+SS_{within}$

We need to find the mean for each group first and the grand mean.

$\bar X =\frac{\sum_{i=1}^n x_i}{n}$

If we apply the before formula we can find the mean for each group

$\bar X_A = 27$ , $\bar X_B = 24$ , $\bar X_C = 30$ . And the grand mean $\bar X = 27$

Now we can find the sum of squares between:

$SS_{between}=SS_{model}=\sum_{j=1}^p n_j (\bar x_{j}-\bar x)^2$

Each group have a sample size of 4 so then $n_j =4$

$SS_{between}=SS_{model}=4(27-27)^2 +4(24-27)^2 +4(30-27)^2=72$

The degrees of freedom for the variation Between is given by $df_{between}=k-1=3-1=2$ , Where k the number of groups k=3.

Now we can find the mean square between treatments (MSTR) we just need to use this formula:

$MSTR=\frac{SS_{between}}{k-1}=\frac{72}{2}=36$

D. 36

Part 3

For the mean square within treatments value first we need to find the sum of squares within and the degrees of freedom.

$SS_{within}=SS_{error}=\sum_{j=1}^p \sum_{i=1}^{n_j} (x_{ij}-\bar x_j)^2$

$SS_{error}=(20-27)^2 +(30-27)^2 +(25-27)^2 +(33-27)^2 +(22-24)^2 +(26-24)^2 +(20-24)^2 +(28-24)^2 +(40-30)^2 +(30-30)^2 +(28-30)^2 +(22-30)^2 =306$

And the degrees of freedom are given by:

$df_{within}=N-k =3*4 -3 = 12-3=9$ . N represent the total number of individuals we have 3 groups each one with a size of 4 individuals. And k the number of groups k=3.

And now we can find the mean square within treatments:

$MSE=\frac{SS_{within}}{N-k}=\frac{306}{9}=34$

C. 34

Part 4

The test statistic F is given by this formula:

$F=\frac{MSTR}{MSE}=\frac{36}{34}=1.059$

B. 1.059

Part 5

The critical value is from a F distribution with degrees of freedom in the numerator of 2 and on the denominator of 9 such that we have 0.01 of the area in the distribution on the right.

And we can use excel to find this critical value with this function:

"=F.INV(1-0.01,2,9)"

And we will see that the critical value is $F_{crit}=8.02$

B. 8.02

5 0

3 years ago