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-Dominant- [34]
3 years ago
9

The amount of kerosene, in thousands of liters, in a tank at the beginning of any day is a random amount Y from which a random a

mount X is sold during that day. Suppose that the tank is not resupplied during the day so that x ? y, and assume that the joint density function of these variables is f(x,y) = 2 for 0 < x < y < 1. find the that the amount of kerosene sold is between 0.25 and 0.50 thousands liters given that the amount in the tank at the start of the day is 0.90 thousands liters. (Hint: f(x|y) = f(x,y) / fy(y) ).

Mathematics
1 answer:
Tems11 [23]3 years ago
5 0

Find the marginal density for Y by integrating the joint PDF over all possible values of x:

f_Y(y)=\displaystyle\int_{-\infty}^\infty f_{X,Y}(x,y)\,\mathrm dx=\int_0^y2\,\mathrm dx

\implies f_Y(y)=\begin{cases}2y&\text{for }0

Then the density of X conditioned on Y is

f_{X|Y}(x\mid y)=\dfrac{f_{X,Y}(x,y)}{f_Y(y)}=\frac1y

for 0 and undefined elsewhere.

Thus

P(0.25

= = =

I'm not seeing the TeX rendering on any of my browsers. Maybe it's a site-wide issue? In any case, I'm attaching a picture of the text above in case it's incomprehensible.

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What is the standard form of 365.05​
pantera1 [17]

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Answer:

  it depends. 365.05  or  3.6505×10²

Step-by-step explanation:

In the US, 365.05 is already in standard form.

In the UK, "standard form" is the same as "scientific notation", so the number would be ...

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3 years ago
50 pts!!!! Luciana's laptop has 3,000 pictures. The size of the pictures is skewed to the right, with a mean of 3.7MB and a stan
skelet666 [1.2K]

Answer:

<u></u>

  • <u>Part A: No, you cannot.</u>

<u></u>

  • <u>Part B: 0.4491</u>

Explanation:

<u>Part A:</u>

The mean of samples of symmetrical (bell shaped) distributions follow a normal distribution pattern.

Thus, for symmetrical distributions you can use the z-score tables to make calculations that permit calculate probabilities for particular values.

For <em>skewed </em>distributions, in general, the samples do not follow a normal distribution pattern, except that the samples are large.

Since <em>a sample of 20 pictures</em> is not large enough, the answer to this question is negative: <em>you cannot accurately calculate the probability that the mean picture size is more than 3.8MB for an SRS (skewed right sample) of 20 pictures.</em>

<u>Part B.</u>

For large samples, the<em> Central Limit Theorem</em> will let you work with samples from skewed distributions.

Although the distribution of a population is skewed, the <em>Central Limit Theorem</em> states that  large samples follow a normal distribution shape.

It is accepted that samples of 30 data is large enough to use the <em>Central Limit Theorem.</em>

Hence, you can use the z-core tables for standard normal distributions to calculate the probabilities for a <em>random sample of 60 pictures</em> instead of 20.

The z-score is calculated with the formula:

  • z-score = (value - mean/ (standard deviation).
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Here, mean = 3.7MB, value = 3.8MB, and standard deviation = 0.78MB.

Thus:

         z=(3.7M-3.8MB)/(0.78MB)=-0.128

Then, you must use the z-score table to find the probability that the z-score is greater than - 0.128.

There are tables that show the cumulative probability in the right end and tables that show the cumulative probability in the left end of a normal standard distribution .

The probability that a z-score is greater than -0.128 is taken directly from a table with the cumulative probability in the left end. It is 0.4491.

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