Please answer this as soon as possible.

he frequency table represents the job status of a number of high school students. A 4-column table with 3 rows titled job status

cluponka [151]

Based on the above, the option that shows the conditional relative frequency table by column is known as option C.

<h3>What is conditional relative frequency table?</h3>

Column conditional relative frequencies is one that is said to be put together or also computed through the act of dividing each frequency in a frequency table by their other column total to form a column conditional relative frequency table.

Note that Column conditional relative frequencies is one that shows the proportions, or relative frequencies, through the use of the column totals and as such the option that tells us about this is option c which is:

A graph that has 4-column table with 3 rows titled job status. The first column has no label with entries currently employed, not currently employed, total. The second column is labeled looking for a job with entries 0.24, 0.76, 1.0. The third column is labeled not looking for a job with entries 0.28, 0.72, 1.0. The fourth column is labeled total with entries nearly equal to 0.27, nearly equal to 0.73, 1.0.

See options below

Which shows the conditional relative frequency table by column?

A. A 4-column table with 3 rows titled job status. The first column has no label with entries currently employed, not currently employed, total. The second column is labeled looking for a job with entries 0.3, nearly equal to 0.33, 1.0. The third column is labeled not looking for job with entries 0.7, nearly equal to 0.65, 1.0. the fourth column is labeled total with entries nearly equal to 0.27, nearly equal to 0.73, 1.0.

B. A 4-column table with 3 rows titled job status. The first column is blank with entries currently employed, not currently employed, total. The second column is labeled Looking for a job with entries 0.12, 0.38, 050. The third column is labeled not looking for a job with entries 0.28, 0.72, 1.00. The fourth column is labeled total with entries 0.4, 1.1, 1.5.

C. A 4-column table with 3 rows titled job status. The first column has no label with entries currently employed, not currently employed, total. The second column is labeled looking for a job with entries 0.24, 0.76, 1.0. The third column is labeled not looking for a job with entries 0.28, 0.72, 1.0. The fourth column is labeled total with entries nearly equal to 0.27, nearly equal to 0.73, 1.0.

D. A 4-column table with 3 rows titled job status. The first column has no label with entries currently employed, not currently employed, total. The second column is labeled looking for job with entries 0.08, nearly equal to 0.25, nearly equal to 0.33. The third column is labeled not looking for a job with entries nearly equal to 0.19, 0.48, nearly equal to 0.67. The fourth column is labeled total with entries nearly equal to 0.27, nearly equal to 0.73, 1.0.

Learn more about relative frequency from

brainly.com/question/3857836

#SPJ1

3 0

2 years ago

Suppose that the data for analysis includes the attributeage. Theagevalues for the datatuples are (in increasing order) 13, 15,

Bas_tet [7]

Answer:

a) $\bar X = \frac{\sum_{i=1}^{27} X_i }{27}= \frac{809}{27}=29.96$

$Median = 25$

b) $Mode = 25, 35$

Since 25 and 35 are repeated 4 times, so then the distribution would be bimodal.

c) $Midrange = \frac{70+13}{3}=41.5$

d) $Q_1 = \frac{20+21}{2} =20.5$

$Q_3 =\frac{35+35}{2}=35$

e) Min = 13 , Q1 = 20.5, Median=25, Q3= 35, Max = 70

f) Figura attached.

g) When we use a quantile plot is because we want to show the percentage or the fraction of values below or equal to an specified value for the distribution of the data.

By the other hand the quantile-quantile plot shows the quantiles of the distribution values against other selected distribution (specified, for example the normal distribution). If the points are on a straight line we assume that the data values fit very well to the hypothetical distribution selected.

Step-by-step explanation:

For this case w ehave the following dataset given:

13, 15, 16, 16, 19, 20, 20, 21, 22, 22, 25, 25, 25, 25, 30,33, 33, 35, 35, 35, 35, 36, 40, 45, 46, 52, 70.

Part a

The mean is calculated with the following formula:

$\bar X = \frac{\sum_{i=1}^{27} X_i }{27}= \frac{809}{27}=29.96$

The median on this case since we have 27 observations and that represent an even number would be the 14 position in the dataset ordered and we got:

$Median = 25$

Part b

The mode is the most repeated value on the dataset on this case would be:

$Mode = 25, 35$

Since 25 and 35 are repeated 4 times, so then the distribution would be bimodal.

Part c

The midrange is defined as:

$Midrange = \frac{Max+Min}{2}$

And if we replace we got:

$Midrange = \frac{70+13}{3}=41.5$

Part d

For the first quartile we need to work with the first 14 observations

13, 15, 16, 16, 19, 20, 20, 21, 22, 22, 25, 25, 25, 25

And the Q1 would be the average between the position 7 and 8 from these values, and we got:

$Q_1 = \frac{20+21}{2} =20.5$

And for the third quartile Q3 we need to use the last 14 observations:

25, 30,33, 33, 35, 35, 35, 35, 36, 40, 45, 46, 52, 70

And the Q3 would be the average between the position 7 and 8 from these values, and we got:

$Q_3 =\frac{35+35}{2}=35$

Part e

The five number summary for this case are:

Min = 13 , Q1 = 20.5, Median=25, Q3= 35, Max = 70

Part f

For this case we can use the following R code:

> x<-c(13, 15, 16, 16, 19, 20, 20, 21, 22, 22, 25, 25, 25, 25, 30,33, 33, 35, 35, 35, 35, 36, 40, 45, 46, 52, 70)

> boxplot(x,main="boxplot for the Data")

And the result is on the figure attached. We see that the dsitribution seems to be assymetric. Right skewed with the Median<Mean

Part g

When we use a quantile plot is because we want to show the percentage or the fraction of values below or equal to an specified value for the distribution of the data.

By the other hand the quantile-quantile plot shows the quantiles of the distribution values against other selected distribution (specified, for example the normal distribution). If the points are on a straight line we assume that the data values fit very well to the hypothetical distribution selected.

6 0

4 years ago

Write an equation in slope-intercept form for the line with slope 8 and y-intercept -8.

Fofino [41]

Answer:

y = 8x - 8

Step-by-step explanation:

y = mx + b is slope-intercept form

m - slope

b - y-intercept

so if you plug in 8 for m and -8 for b you'll get

y = 8(m)x - 8(b)

Hope this helps!!

6 0

3 years ago

Please help and explain

Nesterboy [21]

Answer:

Step-by-step explanation:

Proportional functions are of the form y=kx where k is the constant of proportionality.

k=y/x in this case

k=1008/3.5

k=288

4 0

3 years ago

HELP!<br>A.SSS<br>B.SAS<br>C.ASA<br>D.HL

Harlamova29_29 [7]

The answer is

Read more ......

A.sss

8 0

4 years ago