CH 8 Test 1 Flashcards

1
Q

Individuals

A

are the objects described by a set of data. Individuals may be people, but they may also be animals or things.

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2
Q

variable

A

is any characteristic of an individual. A variable can take different values for different individuals.

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3
Q

categorical variable

A

categorical variable places an individual into one of several groups or categories.

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4
Q

quantitative variable

A

A quantitative variable takes numerical values for which arithmetic operations such as adding and averaging make sense. The values of a quantitative variable are usually recorded with a unit of measurement such as seconds or kilograms.

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5
Q

In a sewing class a teacher assigned the students to make a skirt. As part of the skirt construction, students were required to insert a zipper. In order to assess the students’ sewing skills, the teacher timed how long it took each student to insert his/her zipper. What is the individual in this study?

A. A student

B. Time to insert a zipper

C. A teacher

A

A. A student

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6
Q

Referring to the previous question, what is the variable in this study?

A. Time to insert a zipper

B. A teacher

C. A student

A

A. Time to insert a zipper

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7
Q

exploratory data analysis:

A

Use of graphs and numerical summaries to describe the variables in a data set and the relations among them.

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8
Q

Exploring Data

A
  1. Begin by examining each variable by itself. Then move on to study the relationships among the variables.
  2. Begin with a graph or graphs. Then add numerical summaries of specific aspects of the data.
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9
Q

distribution:

A

Tells us what values a variable takes and how often it takes these values.

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10
Q

roundoff error

A

It’s a good idea to check data for consistency. The percents should add to 100%. In fact, they add to 100.1%. What happened? Each percent is rounded to the nearest tenth. The exact percents would add to 100, but the rounded percents only come close. This is roundoff error.roundoff error Roundoff errors don’t point to mistakes in our work, just to the effect of rounding off results.

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11
Q

Pie charts

A

pie charts show the distribution of a categorical variable as a “pie” whose slices are sized by the counts or percents for the categories. A pie chart must include all the categories that make up a whole. Use a pie chart only when you want to emphasize each category’s relation to the whole.

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12
Q

Bar graphs

A

bar graphs represent each category as a bar. The bar heights show the category counts or percents. Bar graphs are easier to make than pie charts and also easier to read.
it is often better to arrange the bars in order of height. Bar graphs are more flexible than pie charts. Both graphs can display the distribution of a categorical variable, but a bar graph can also compare any set of quantities that are measured in the same units.

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13
Q

histogram:

A

A graph of the distribution of one quantitative variable. To construct, first divide the range of the data into classes of equal width. Next, count the individuals in each class. Then mark the horizontal axis in the units of measurement for the variable. The vertical axis contains the scale of counts. Each bar represents a class. The base of the bar covers the class, and the bar height is the class count.

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