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2 years ago

Consider the following graph, which details one bookstore’s sales over the course of one day, divided by genre.

Mathematics

2 answers:

Crazy boy [7]2 years ago

5 0

The percent by which the sales of horror books is greater than sales of cookbook is 1.85% approx.

<h3>How to find the percentage from the total value?</h3>

Suppose the value of which a thing is expressed in percentage is "a'

Suppose the percent that considered thing is of "a" is b%

Then since percent shows per 100 (since cent means 100), thus we will first divide the whole part in 100 parts and then we multiply it with b so that we collect b items per 100 items(that is exactly what b per cent means).

Thus, that thing in number is

$\dfrac{a}{100} \times b$

Given that:

Genre number sold

Romance 52
Horror 55
Fantasy 60
Biography 57
Humor 58
Cookbook 54

Let we have:
Number of horror books sold = P% greater than number of cookbooks sold

55 = P% greater than 54

55 = 54 + P% of 54

1 = P% of 54

$1 = \dfrac{P}{100} \times 54\\\\P = \dfrac{100}{54} \approx 1.85$

Thus, the percent by which the sales of horror books is greater than sales of cookbook is 1.85% approx.

Learn more about percent here:

brainly.com/question/11549320

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NNADVOKAT [17]2 years ago

4 0

Answer:

Say that you put the set of tiles shown below into a bag and conduct a series of trials in which you draw one tile randomly from the bag, record the color, and replace it. The table below shows the number of times in each set of trials that you drew a blue tile.

Round tiles: 5 purple, 6 orange, 2 yellow, 4 red, 1 white, 10 blue, 5 black, 3 green.

Trial

# of Draws

# of Blues

Between the theoretical probability that you will draw a blue tile and the experimental probability that you will draw a blue tile, which is greater, and how much greater is it? Express all probabilities as percentages to two decimal places, and express differences by number of percentage points (for example, 12% is 2 percentage points greater than 10%).

The theoretical probability is 2.78 percentage points greater than the experimental probability.

The theoretical probability is 1.49 percentage points greater than the experimental probability.

The experimental probability is 4.06 percentage points greater than the theoretical probability.

<h2><u>d.</u></h2><h2><u>The experimental probability is 2.17 percentage points greater than the theoretical probability. <<<CORRECT</u></h2>

Step-by-step explanation:

Edge 2022

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Choose the possible descriptions of cross sections formed by the intersection of a plane and a cylinder choose all that apply

nasty-shy [4]

Answer:

circle and rectangle

Step-by-step explanation:

we know that

A cross section that is perpendicular to the base of cylinder is a rectangle

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3 years ago

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Veronika [31]

Answer:

99% of the sample means will fall between 0.93288 and 0.94112.

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 $\mu$ and standard deviation $\sigma$ , the z-score 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 p-value, 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 normally distributed random variable X, with mean $\mu$ and standard deviation $\sigma$ , the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean $\mu$ and standard deviation $s = \frac{\sigma}{\sqrt{n}}$ .

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

The true mean is .9370 with a standard deviation of 0.0090

This means that $\mu = 0.9370, \sigma = 0.0090$

Sample of 32:

This means that $n = 32, s = \frac{0.009}{32} = 0.0016$

Within what interval will 99 percent of the sample means fall?

Between the 50 - (99/2) = 0.5th percentile and the 50 + (99/2) = 99.5th percentile.

0.5th percentile:

X when Z has a pvalue of 0.005. So X when Z = -2.575.

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

By the Central Limit Theorem

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

$-2.575 = \frac{X - 0.9370}{0.0016}$

$X - 0.9370 = -2.575*0.0016$

$X = 0.93288$

99.5th percentile:

X when Z has a pvalue of 0.995. So X when Z = 2.575.

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

$2.575 = \frac{X - 0.9370}{0.0016}$

$X - 0.9370 = 2.575*0.0016$

$X = 0.94112$

99% of the sample means will fall between 0.93288 and 0.94112.

6 0

3 years ago

Am not the smartest can someone help me.

Anit [1.1K]

Answer:

4 7/10

Step-by-step explanation:

4 0

3 years ago

Read 2 more answers

Let be the density function for the shelf life of a brand of banana which lasts up to weeks. Time, , is measured in weeks and .

Maurinko [17]

The question is incomplete. The complete question is :

Let $p(t) = -0.0375t^2 + 0.225t$ be the density function for the shelf life of a brand of banana which lasts up to 4 weeks. Time, t, is measured in weeks and $0 \leq t \leq 4$ . Incorrect answer icon Your answer is incorrect. Find the mean shelf life of a banana using . Round your answer to one decimal place.