Organizing Data Categorical/Qualitative Quantitative: Discreet and Continuous.

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Organizing Data Categorical/Qualitative Quantitative: Discreet and Continuous

Transcript of Organizing Data Categorical/Qualitative Quantitative: Discreet and Continuous.

Page 1: Organizing Data Categorical/Qualitative Quantitative: Discreet and Continuous.

Organizing Data

Categorical/QualitativeQuantitative: Discreet and Continuous

Page 2: Organizing Data Categorical/Qualitative Quantitative: Discreet and Continuous.

Qualitative Data

• Data that can be identified as non-numerical

Example:a) Genderb) Subjects taught in high schoolc) Leading causes of cancerd) Nationally recognized holidays

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Quantitative Data• Data that can be identified as numerical, which

implies that it can be ranked in some way.

Example:a) Grade point averagesb) Bowling scoresc) Rankings of major cities in crime preventiond) Prices of gasoline at different service stations

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Quantitative Data - Discreet• Data that can be assigned a specific value and

can be counted.Example:a) The number of children in a classroomb) The annual salary of a person (in whole $)c) The number of months in a yeard) Attendance at a concert

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Quantitative Data - Continuous• Data that can be obtained by measuring, not

by countingExample:a) The temperature at different times of the dayb) The weight of each player on a football teamc) The number of gallons of water in different

swimming poolsd) The heights of adults at a party

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Quantitative Data - Continuous• Data that can be obtained by measuring, not

by counting

This data is an estimation. If we claim that a person weighs 160 pounds, we recognize that our accuracy is only as good as the scale that is being used.

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Quantitative Data - Continuous• Data that can be obtained by measuring, not

by counting

This data is an estimation. Suppose that your time was clocked at 11.2 seconds for a 100-yard dash. It is possible that your time was closer to 11.22 seconds or even 11.19 seconds.

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Presumptions of Continuous Data• When continuous data is used, there are

presumed boundaries associated with the given value.

• 159.5 160160.5

We would include the lower boundary because the nearest pound, 159.5 rounds off to 160, but 160.5 would actually round off to 161.

Boundaries are written as intervals:159.5 – 160.5

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Technique used to establish boundaries?

Rules Lower boundary

Data Upper boundary

Integer xx – 0.5x + 0.5

9

Tenths x – 0.05X + 0.05

9.1

8.5 9.5

9.05 9.15

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What are the boundaries for 52.81?

52.805 – 52.815Remember that 52.805 is included in

this interval, but 52.815 is not included.

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What are the boundaries for 33.0?

32.95 – 33.05Be careful here! Even though 33.0

has the same numerical value as 33, the given measurement is shown to be accurate to the nearest tenth.

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The length of a stapler is measured to be 4.85 inches. How many of the following numbers

would be included in the interval containing the associated boundaries?

4.848 4.855 4.8449 4.94.8452Interval:

4.845 and 4.855 Be sure to

understand that the upper boundary of

4.855 is not included

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Which one(s) of the following are representative of qualitative data?

1. time needed to complete a project2. number of houses in a city block3. depth of an ocean4. blood type

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Numbers such as Social Security numbers, house addresses, and company badge

numbers are also considered qualitative data.

They contain numbers but there is no ranking system involved. One SS# has no greater value than another SS#

Math Flash!!!

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Organize Data in Pie Graph (pie chart/circle graph)

• Pie graph is best to use when we are looking at the percent contribution of the component of the component parts of a particular category.

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In the Growing Strong Hospital, a survey was taken of the marital status of each employee. The results showed that 20% are married with no children, 25% are married with at least one

child, 15% are single, 30% are divorced, and the remaining 10% are widowed. Create an

appropriate pie graph.

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• Married with No Children: (0.20)(3600)=720

• Married with at Least One Child: (0.25)(3600)=900

• Single: (0.15)(3600)=540

• Divorced: (0.30)(3600)=1080

• Widowed: (0.10)(3600)=360

The sum of the degrees in each category is 3600

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Label each category of the graph by percent

not by degree.

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Suppose there are a total of 1500 employees in the Growing Strong Hospital.

How many of them are either single or divorced?

Percent of single employees + divorced employees

15%+ 30% = 45%

1500(0.45)= 675 employees