What is 66 2/3 % times $48

What is the sum of (2x+4)+(-3x+9)

Levart [38]

Answer:

-x + 13

General Formulas and Concepts:

Pre-Algebra

Order of Operations: BPEMDAS

Brackets
Parenthesis
Exponents
Multiplication
Division
Addition
Subtraction

Left to Right

Algebra I

Combining Like Terms

Step-by-step explanation:

Step 1: Define expression

(2x + 4) + (-3x + 9)

Step 2: Simplify

Combine like terms (x): -x + 4 + 9
Combine like terms (Z): -x + 13

7 0

2 years ago

Read 2 more answers

HELP I NEED HELP ASAP

Kaylis [27]

Answer:

so how many units are they away from each other

Step-by-step explanation:1,

1.1-2.0 how many units are they away from each other

u could drag the number from the top to the chart below

good luck!

6 0

3 years ago

Which of the following is the product of the rational expression shown below

wolverine [178]

Option C: $\frac{x^{2}-9}{x^{2}-4}$ is the product of the rational expression.

Explanation:

The given rational expression is $\frac{x+3}{x+2} \cdot \frac{x-3}{x-2}$

We need to determine the product of the rational expression.

Product of the rational expression:

Let us multiply the rational expression to determine the product of the rational expression.

Thus, we have;

$\frac{(x+3)(x-3)}{(x+2)(x-2)}$

Let us use the identity $(a+b)(a-b)=a^2-b^2$ in the above expression.

Thus, we get;

$\frac{x^{2} -3^2}{x^{2} -2^2}$

Simplifying the terms, we get;

$\frac{x^{2}-9}{x^{2}-4}$

Thus, the product of the rational expression is $\frac{x^{2}-9}{x^{2}-4}$

Hence, Option C is the correct answer.

6 0

3 years ago

An article reports the following data on yield (y), mean temperature over the period between date of coming into hops and date o

skelet666 [1.2K]

Answer:

x1=c(16.7,17.4,18.4,16.8,18.9,17.1,17.3,18.2,21.3,21.2,20.7,18.5)

x2=c(30,42,47,47,43,41,48,44,43,50,56,60)

y=c(210,110,103,103,91,76,73,70,68,53,45,31)

mod=lm(y~x1+x2)

summary(mod)

R output: Call:

lm(formula = y ~ x1 + x2)

Residuals:

Min 1Q Median 3Q Max

-41.730 -12.174 0.791 12.374 40.093

Coefficients:

Estimate Std. Error t value Pr(>|t|)

(Intercept) 415.113 82.517 5.031 0.000709 ***

x1 -6.593 4.859 -1.357 0.207913

x2 -4.504 1.071 -4.204 0.002292 **

---

Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 24.45 on 9 degrees of freedom

Multiple R-squared: 0.768, Adjusted R-squared: 0.7164

F-statistic: 14.9 on 2 and 9 DF, p-value: 0.001395

a). y=415.113 +(-6.593)x1 +(-4.504)x2

b). s=24.45

c). y =415.113 +(-6.593)*21.3 +(-4.504)*43 =81.0101

residual =68-81.0101 = -13.0101

d). F=14.9

P=0.0014

There is convincing evidence at least one of the explanatory variables is significant predictor of the response.

e). newdata=data.frame(x1=21.3, x2=43)

# confidence interval

predict(mod, newdata, interval="confidence")

#prediction interval

predict(mod, newdata, interval="predict")

confidence interval

> predict(mod, newdata, interval="confidence",level=.95)

fit lwr upr

1 81.03364 43.52379 118.5435

95% CI = (43.52, 118.54)

f). #prediction interval

> predict(mod, newdata, interval="predict",level=.95)

fit lwr upr

1 81.03364 14.19586 147.8714

95% PI=(14.20, 147.87)

g). No, there is not evidence this factor is significant. It should be dropped from the model.

4 0

2 years ago

This is due today, and I have no idea what I'm doing, please help if you know anything.

defon

Binomial distribution formula: P(x) = (n k) p^k * (1 - p)^n - k

a) Probability that four parts are defective = 0.01374

P(4 defective) = (25 4) (0.04)^4 * (0.96)^21

P(4 defective) = 0.01374

b) Probability that at least one part is defective = 0.6396

Find the probability that 0 parts are defective and subtract that probability from 1.

P(0 defective) = (25 0) (0.04)^0 * (0.96)^25

P(0 defective) = 0.3604

1 - 0.3604 = 0.6396

c) Probability that 25 parts are defective = approximately 0

P(25 defective) = (25 25) (0.04)^25 * (0.96)^0

P(25 defective) = approximately 0

d) Probability that at most 1 part is defective = 0.7358

Find the probability that 0 and 1 parts are defective and add them together.

P(0 defective) = 0.3604 (from above)

P(1 defective) = (25 1) (0.04)^1 * (0.96)^24

P(1 defective) = 0.3754

P(at most 1 defective) = 0.3604 + 0.3754 = 0.7358

e) Mean = 1 | Standard Deviation = 0.9798

mean = n * p

mean = 25 * 0.04 = 1

stdev = $\sqrt{np(1-p)}$

stdev = $\sqrt{(25)(0.04)(1-0.04)}$ = 0.9798

Hope this helps!! :)

7 0

3 years ago