What is the value of k ?

A convenience store purchased a magazine and marked it up 100% from the original cost of $2.30. A week later, the store placed t

77julia77 [94]

Answer:

$2.30

Step-by-step explanation:

The original price is $2.30 an it goes up by 100% which means another 2.30. So add 2.30 and 2.30 together you get 4.60 now divide that by two since the magazine is 50% off and you get the original price which was 2.30

5 0

3 years ago

Read 2 more answers

Which function is a translation of the parent absolute value function?

Veronika [31]

Answer:

$g(x) = |x-5|-4$

Step-by-step explanation:

$f(x) = |x|\\\\g(x) = f(x-5)-4\\\\g(x) = |x-5|-4$

7 0

3 years ago

A parabola intersects the x-axis at x=3, equals, 3 and x=9.

kakasveta [241]

Answer: x is 6

Step-by-step explanation:

where a and b are x intercepts given to us.

So rewriting in factored form:

y = ( $x-3$ )( $x-9$ )

so now you have to simplify it using the formula $y=$ $ax^{2}$ $+$ $bx-c$

y= $x^{2}$ - $12x$ + $27$

so with this formula $x=\frac{-b}{2a}$ we can find the x coordinate

$x=\frac{-(-12)}{2(1)}$

and the answer would be 6

8 0

3 years ago

A manufacturer knows that their items have a normally distributed length, with a mean of 13.1 inches, and standard deviation of

Afina-wow [57]

Answer:

0.73% probability that their mean length is less than 11.1 inches

Step-by-step explanation:

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

Normal probability distribution:

Problems of normally distributed samples are solved using the z-score formula.

In a set with mean $\mu$ and standard deviation $\sigma$ , the zscore of a measure X is given by:

$Z = \frac{X - \mu}{\sigma}$

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 pvalue, we get the probability that the value of the measure is greater than X.

Central limit theorem:

The Central Limit Theorem estabilishes that, for a random variable X, with mean $\mu$ and standard deviation $\sigma$ , a large sample size can be approximated to a normal distribution with mean $\mu$ and standard deviation, which is also called standard error $s = \frac{\sigma}{\sqrt{n}}$