How to calculate cumulative frequency

That's a pretty vague question, but the answer is a cumulative frequency table is exactly the data you'd need for a histogram. A histogram is a chart where for each class or range of data you display a count of how many times you had a sample data point in that range.

Let's say you were measuring heights of seventh graders. We might make our ranges the following:

<60 in

60-63

63-66

66-69

69-72

>72 in

Then we'd measure some seventh graders and get data like:

62.1 67.8 65.5 63.0 69.1 64.2 65.8 63.2 62.8 69.4

We'd make our cumulative frequency table by counting how many in each range. We have to decide about 63.0, on the line; let's put it in 63-66.

range count

<60 in 0

60-63 2

63-66 5

66-69 1

69-72 2

>72 in 0

The frequency is the ratio of the count to n, the total count, here n=10 heights. So we can add the frequency column where we divide the counts by 10 and express the result as a percentage.

range count freq

<60 in 0 0%

60-63 2 20%

63-66 5 50%

66-69 1 10%

69-72 2 20%

>72 in 0 0%

That's how you make a cumulative frequency table where you calculate the frequency of a number of ranges. It can also be used for categorical data; we count each category.

85.560%

step-by-step explanation:

conditional probability is defined as:

p(a|b) = p(a∩b) / p(b)

in other words, the probability that a occurs, given that b has occurred = the probability that both a and b occur / the probability that b occurs.

in this example:

p(turns 64 | turns 44) = p(turns 64 & turns 44) / p(turns 44).

if someone turns 64, they must have already turned 44, so:

p(turns 64 | turns 44) = p(turns 64) / p(turns 44)

on page 42, we see that of the original 100,000, 94944 turn 44, and 81234 turn 64.   therefore:

p(turns 64 | turns 44) = 81234 / 94944

p(turns 64 | turns 44) = 0.85560

if the probability is 1/12, 75 people will receive a $25 gift card

step-by-step explanation: