What is Relative Frequency

What is Relative FrequencyThe relative frequency is not any theoretical quantity, however an experimental one. We have to repeat an experiment several times and count the number of times the result of the trial is in the event set. Since it is experimental, it is possible to have a different relative frequency each time that we repeat an experiment.

The relative frequency depends upon the series of outcomes that we notice while carrying out a statistical experiment. The relative frequency could be different each time we redo the test. The more trials we run throughout an experiment, the nearer the observed relative frequency of an event will reach the theoretical probability of an event.

Relative Frequency Histogram

A relative frequency histogram makes use of the same information like a frequency histogram however compares every class interval to the whole number of items. For instance, the first interval ($1 to $5) includes 8 out of the total of 32 products, so the relative frequency of the initial class interval is 8/32

The only distinction between a frequency histogram and a relative frequency histogram is always that the vertical axis utilizes relative or proportional frequency rather than simple frequency.

Relative frequency histogram of products sold at a garage sale.

How to Find Relative Frequency

Frequency is a simple concept to know. The count of the number of data values fall under a specific class make up the frequency for this class. Classes with lower frequencies have lesser bars and classes with higher frequencies have greater bars.

Relative frequency needs one step more. Relative frequency is actually a measure of what proportion or percent from the data values fall under a particular class. A easy calculation determines the relative frequency through the frequency. All that we have to do is add up all the frequencies. Then we divide the count from every class by the amount of the frequencies.

To find out the relative frequency for every class we very first add the total number of data points: 7 + 9 + 18 + 12 + 4 = 50. We next divide each frequency by this amount 50.

0.14 = 14% students with an F

0.18 = 18% students with a D

0.36 = 36% students with a C

0.24 = 24% students with a B

0.08 = 8% students with an A

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