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Ronch [10]
4 years ago
12

Am I correct if not please help me

Mathematics
1 answer:
vesna_86 [32]4 years ago
4 0
You are correct Chloe Karus
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Construct a frequency distribution and a relative frequency distribution for the light bulb data with a class width of 20, start
k0ka [10]

Answer:

Step-by-step explanation:

Hello!

You have the information about light bulbs (i believe is their lifespan in hours) And need to organize the information in a frequency table.

The first table will be with a class width of 20, starting with 800. This means that you have to organize all possible observations of X(lifespan of light bulbs) in a class interval with an amplitude of 20hs and then organize the information noting their absolute frequencies.

Example

1) [800;820) only one observation classifies for this interval x= 819, so f1: 1

2)[820; 840) only one observation classifies for this interval x= 836, so f2: 1

3)[840;860) no observations are included in this interval, so f3=0

etc... (see attachment)

[ means that the interval is closed and starts with that number

) means that the interval is open, the number is not included in it.

fi: absolute frequency

hi= fi/n: relative frequency

To graph the histogram you have to create the classmark for each interval:

x'= (Upper bond + Lower bond)/2

As you can see in the table, there are several intervals with no observed frequency, this distribution is not uniform least to say symmetric.

To check the symmetry of the distribution is it best to obtain the values of the mode, median and mean.

To see if this frequency distribution has one or more modes you have to identify the max absolute frequency and see how many intervals have it.

In this case, the maximal absolute frequency is fi=6 and only one interval has it [1000;1020)

Mo= LB + Ai (\frac{D_1}{D_1+D_2} )\\

LB= Lower bond of the modal interval

D₁= fmax - fi of the previous interval

D₂= fmax - fi of the following interval

Ai= amplitude of the modal interval

Mo= 1000 + 20*(\frac{(6-3)}{(6-3)+(6-4)} )=1012

This distribution is unimodal (Mo= 1012)

The Median for this frequency:

Position of the median= n/2 = 40/2= 20

The median is the 20th fi, using this information, the interval that contains the median is [1000;1020)

Me= LB + Ai*[\frac{PosMe - F_{i-1}}{f_i} ]

LB= Lower bond of the interval of the median

Ai= amplitude of the interval

F(i-1)= acumulated absolute frequency until the previous interval

fi= absolute frequency of the interval

Me= 1000+ 20*[\frac{20-16}{6} ]= 1013.33

Mean for a frequency distribution:

X[bar]= \frac{sum x'*fi}{n}

∑x'*fi= summatory of each class mark by the frequency of it's interval.

∑x'*fi= (810*1)+(230*1)+(870*0)+(890*2)+(910*4)+(930*0)+(950*4)+(970*1)+(990*3)+(1010*6)+(1030*4)+(1050*0)+(1070*3)+(1090*2)+(1110*4)+(1130*0)+(1150*2)+(1170*1)+(1190*1)+(1210*0)+(1230*1)= 40700

X[bar]= \frac{40700}{40} = 1017.5

Mo= 1012 < Me= 1013.33 < X[bar]= 1017.5

Looking only at the measurements of central tendency you could wrongly conclude that the distribution is symmetrical or slightly skewed to the right since the three values are included in the same interval but not the same number.

*-*-*

Now you have to do the same but changing the class with (interval amplitude) to 100, starting at 800

Example

1) [800;900) There are 4 observations that are included in this interval: 819, 836, 888, 897 , so f1=4

2)[900;1000) There are 12 observations that are included in this interval: 903, 907, 912, 918, 942, 943, 952, 959, 962, 986, 992, 994 , so f2= 12

etc...

As you can see this distribution is more uniform, increasing the amplitude of the intervals not only decreased the number of class intervals but now we observe that there are observed frequencies for all of them.

Mode:

The largest absolute frequency is f(3)=15, so the mode interval is [1000;1100)

Using the same formula as before:

Mo= 1000 + 100*(\frac{(15-12)}{(15-12)+(15-8)} )=1030

This distribution is unimodal.

Median:

Position of the median n/2= 40/2= 20

As before is the 20th observed frequency, this frequency is included in the interval [1000;1100)

Me= 1000+ 100*[\frac{20-16}{15} ]= 1026.67

Mean:

∑x'*fi= (850*4)+(950*12)+(1050*15)+(1150*8)+(1250*1)= 41000

X[bar]= \frac{41000}{40} = 1025

X[bar]= 1025 < Me= 1026.67 < Mo= 1030

The three values are included in the same interval, but seeing how the mean is less than the median and the mode, I would say this distribution is symmetrical or slightly skewed to the left.

I hope it helps!

8 0
4 years ago
If you flip a coin ten times and get tails three times; what is the experimental probability of getting heads?
kirill115 [55]

Answer:

50 goes to 25 to 12.5 then 6.25%

Step-by-step explanation:

i hope i helped

6 0
4 years ago
#13: The difference between two numbers is 3. Their sum if 27. What is the smaller number? * Your answer​
Lelu [443]

Answer:

The smaller number is 12 & greater number is 15.

8 0
3 years ago
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Which property of equity would you use to solve the equation x/5=13
AveGali [126]

Answer: subtraction property.

Step-by-step explanation:

3 0
4 years ago
The results of a national survey showed that on average, adults sleep 6.7 hours per night. Suppose that the standard deviation i
Roman55 [17]

Answer:

a) Atleast 75%

b) Atleast 88.9%

c) 95%

Step-by-step explanation:

We are given the following information in the question:

Mean, μ = 6.7

Standard Deviation, σ = 1.6

Chebyshev's Theorem:

  • Atleast 1 - \dfrac{1}{k^2} percent of data lies within k standard deviation of mean.

Empirical Rule:

  • Almost all the data lies within 3 standard deviation for a normal data.
  • Around 68% of data lies within 1 standard deviation of mean.
  • Around 95% of data lies within 2 standard deviation of mean.
  • Around 99.7% of data lies within 3 standard deviations o mean.

a) minimum percentage of individuals who sleep between 3.5 and 9.9 hours

3.5 = \mu - 2\sigma = 6.7 - 2(1.6)\\9.9 = \mu + 2\sigma = 6.7 + 2(1.6)

We have to find the percent of data lying within 2 standard deviation of mean.

Putting k =  2

1 - \dfrac{1}{(2)^2} = 0.75 = 75\%

Atleast 75% of of individuals who sleep between 3.5 and 9.9 hours.

b) minimum percentage of individuals who sleep between 2.7 and 10.7 hours

2.7 = \mu - 3\sigma = 6.7 - 3(1.6)\\10.7 = \mu + 3\sigma = 6.7 + 3(1.6)

We have to find the percent of data lying within 3 standard deviation of mean.

Putting k =  3

1 - \dfrac{1}{(3)^2} = 0.889 = 88.9\%

Atleast 88.9% of of individuals who sleep between 2.7 and 10.7 hours.

c)  percentage of individuals who sleep between 3.5 and 9.9 hours per day.

Thus, we have to find the percentage of data lying within 2 standard deviation.

By empirical rule, around 95% of data lies within 2 standard deviation.

Thus, 95% of of individuals who sleep between 3.5 and 9.9 hours.

This is higher than the percentage obtained from Chebyshev's rule.

4 0
3 years ago
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