a flashlight has 6 batteries, 2 are defective. what is the probability you select at least 1 good battery

Please helppp fast!!Simplify (4x^5)^2 (x^10)^1/2

Oksi-84 [34.3K]

Answer:

(4^2*x7)(x^10.5)

8 0

3 years ago

Which ordered pair is a solution of the equation y=7x-3

Kruka [31]

Im pretty sure its (1, 4) if its wrong im so so sorry but I do think thats the awnser

5 0

3 years ago

Can anyone help solve this equation?

koban [17]

Answer:

13

Step-by-step explanation:

3 x 3 = 9

7 + 3 = 10

7 + ? = 3 + 7 + 3 + 7

7 + ? = 20

? = 13

3 0

3 years ago

Read 2 more answers

The Frosty Ice-Cream Shop sells sundaes for $2 and banana splits for $3. On a hot summer day, the shop sold 8 more sundaes than

svlad2 [7]

The shop sold 36 sundaes and 28 banana spilts

Solution:

Let "a" be the number of sundaes sold

Let "b" be the number of banana spilts sold

Cost of 1 sundaes = $ 2

Cost of 1 banana spilt = $ 3

On a hot summer day, the shop sold 8 more sundaes than banana splits and made $156

Therefore,

Number of sundaes sold = 8 + number of banana spilts sold

a = 8 + b ------- eqn 1

Also, given that they made $ 156

Therefore, we frame a equation as:

Number of sundaes sold x Cost of 1 sundaes + number of banana spilts sold x Cost of 1 banana spilt = 156

$a \times 2+b \times 3 = 156$

2a + 3b = 156 ---------- eqn 2

Substitute eqn 1 into eqn 2

2(8 + b) + 3b = 156

16 + 2b + 3b = 156

16 + 5b = 156

5b = 156 - 16

5b = 140

Substitute b = 28 in eqn 1

a = 8 + 28

Thus the shop sold 36 sundaes and 28 banana spilts

4 0

3 years ago

In a study relating the degree of warping, in mm, of a copper plate (y) to temperature in °C (x), the following summary statisti

kipiarov [429]

Answer:

The error sum of squares is SSE=12.97

The regression sum of squares is SSR=6.430

The total sum of squares is SST=19.4

Step-by-step explanation:

Linear regression is a way "to modeling the relationship between a scalar response (or dependent variable) and one or more explanatory variables (or independent variables)".

Regression estimates are "used to describe data and to explain the relationship between one dependent variable and one or more independent variables"

The linear model is given by the following equation $Y=mx +b$ , where y is the dependent variable, x the independent variable, m the slope and b the intercept.