Chapter 1 - Describing Graphs with Data Flashcards

1
Q

a characteristic that changes or varies over time and/or for different individuals or objects under consideration

A

Variable

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2
Q

Hair color, white blood cell count, time to failure of a computer component, Apple stock price (over time) These are examples of?

A

Variables

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3
Q

the individual or object on which a variable is measured

A

Experimental Unit

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4
Q

results when a variable is actually measured on an experimental unit

A

a Measurement

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5
Q

A set of measurements called __, can be either a __ or a ___

A

data sample population

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6
Q

Each of these are an example of:

1) Hair color
2) Person
3) Brown, black, blonde, etc.

A

1) Variable 2) Experimental unit 3) Typical Measurements

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7
Q

Each of these are an example of: 1) Time until a light bulb burns out 2) light bulb 3) 1500 hours, 1535.5 hours, etc.

A

1) Variable 2) Experimental unit 3) Typical Measurements

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8
Q

One variable is measured on a single experimental unit

A

Univariate Data

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9
Q

Two variables are measured on a single experimental unit

A

Bivariate Data

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10
Q

More than two variables are measured on a single experimental unit

A

Multivariate Data

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11
Q

Types of Variables

A

1) Qualitative 2) Quantitative

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12
Q

Types of Quantitative Variables

A

a) discrete b) continuous

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13
Q

measure a quality or characteristic on each experimental unit.

A

Qualitative (categorical) Variables

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14
Q

measure a numerical quantity on each experimental unit

A

Quantitative Variables

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15
Q

if it can assume only a finite or countable number of values

A

Discrete Quantitative Variable

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16
Q

if it can assume the infinitely many values corresponding to the points on a line interval

A

Continuous Quantitative Variable

17
Q

For each orange tree in a grove, the number of oranges is measured.

A

Quantitative discrete

18
Q

For a particular day, the number of cars entering a college campus is measured.

A

Quantitative discrete

19
Q

Time until a light bulb burns out

A

Quantitative continuous

20
Q

Graphing Qualitative Variables 1) Qualitative Variables use a ___ ___ to describe: a) b)

A

1) Data Distribution a) WHAT VALUES of the variable have been measured b) HOW OFTEN each value has occurred

21
Q

“How Often” can be measured in (3) ways

A

1) Frequency 2) Relative frequency = Frequency/n ( n=sample size) 3) Percent = 100 x Relative frequency

22
Q

Relative Frequency Equation

A

Frequency/n ( n=sample size)

23
Q

Percent Equation

A

100 x Relative Frequency

24
Q

A single quantitative variable measured for different population segments or for different categories of classification can be graphed using?

A

a PIE or BAR chart

25
Q

Dotplot how to make one?

A

Plots the measurements as points on a horizontal axis, stacking the points that duplicate existing points.

26
Q

Dotplot for what type of data?

A

Quantitative data

27
Q

Stem and Leaf Plots for what type of data?

A

Quantitative data

28
Q

Stem and Leaf Plot 1) Divide each measurement into two parts: the __ and the __. 2) List the stems in a __, with a __ __ to their __. 3) For each measurement, record the __ __ in the __ __ as its __ __. 4) Order the leaves from __ to __ in each __. 5) Provide a __ to your coding.

A

1) Stem and the Leaf 2) In a Column, Vertical Line to their Right 3) Leaf portion, same row, matching stem 4) lowest to highest in each stem 5) key

29
Q

1) A single quantitative variable measured over time is called a
2) It can be graphed using a __ or a ___ ___.

A

1) Time Series
2) Line or Bar Chart

30
Q

Dotplot for the data set: 4, 5, 5, 7, 6

31
Q

Stem and Leaf Plot for Data:

The prices ($) of 18 brands of walking shoes:
90 70 70 70 75 70 65 68 60
74 70 95 75 70 68 65 40 65

32
Q

Which Shapes are each of these graphs:

A

1) mound shaped & symmetric (mirror image)
2) Skewed right: a few unusually large measurements
3) Skewed left: a few unusually small measurements
4) Bimodal: two local peaks

33
Q

Strange or unusual measurements that stand out in the data set

34
Q

Relative Frequency Histogram

1) for what type of data set?
2) what type of graph
3) height of the bar shows?
4) hows it measured?

A

1) quantitative data
2) bar graph
3) the height of the bar shows “how often” measurements fall in a particular class or subinterval.
4) measured as a proportion or relative frequency

35
Q

How to make a Relative Frequency Histogram

36
Q

Relative Frequency Histograms

1) Divide the range of the data into __ ____ of equal length.
2) Calculate the __ __ of the subinterval as Range/number of subintervals.
3) Round the approximate __ up to a convenient value.
4) Use the method of __ __, including the __ endpoint, but not the __ in your __.
5) Create a statistical table including the __, their __ and __ __ .

A

1) 5-12 subintervals
2) approximate width
3) width
4) left inclusion, left, right, tally
5) subintervals, frequencies, relative frequencies

37
Q

Relative Frequency Histogram

1) horizontal axis
2) vertical axis

A

1) subintervals
2) relative frequency

38
Q

Relative Frequency Histograms

height of the bar represents?

A

PROPORTION of measurements falling in that class or subinterval

PROBABILITY that a single measurement , drawn at random from the set, will belong to that class