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Statistics > CHAPTER 4 Displaying and summarizing quantitative data > Flashcards

CHAPTER 4 Displaying and summarizing quantitative data Flashcards

1
Q

How are quantitative data represented

A

1.HISTOGRAM
. The Horizontal axis the bins are joined together with equal widths
. It is a summary of the distribution of quantitative variable but they don;t show the data values themselves
2. STEM AND LEAF
3. DOTPLOTS

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2
Q

RELATIVE FREQUENCY HISTOGRAMS

A

replaces the counts on the vertical axis with the percentage of the total number of cases falling in each bin.
. The Horizontal axis the bins are joined together with equal widths

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3
Q

STEM AND LEAF

A

Is like a histogram, but shows the individual values

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4
Q

DOT PLOTS

A

A simple display that places a dot along an axis for each case in the data ( similar to stem and leaf)

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5
Q

QUANTITATIVE DATA CONDITION

A

Values of quantative variables whose units are known

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6
Q

MODE

A

SINGLE VALUE THAT APPEARS MOST OFTEN ( for categorical values)
. for quantitative it is the HUMPS ( UNIMODAL, BIMODAL, MULIMODAL, UNIFORM)

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7
Q

Uniform

A

Is a histogram in which all the bars are approximately the same height

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8
Q

TAILS

A

the thinner ends of a histogram

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9
Q

SKEWED

A

if one TAIL stretches out further than another. the graph is skewed toward the longer tail

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10
Q

OUTLIERS

A

Extreme values that don’t appear to belong to the rest of the data… unsually high oe low values

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11
Q

GAP

A

A region that has no values

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12
Q

CENTER OF MEASURE

A

A single, typical value of a data set

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13
Q

2 types of Center of Measure

A
  1. Mean

2. Median

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14
Q

MEDIAN

A

The middle value

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15
Q

IQR

A

Upper percentile- lower percentile

It is a reasonable summary of the spread of a distribution except when the dat is strongly bimodal

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16
Q

Q1( lower) and Q3( upper)

A

are also known as the 25th and 75th percentiles of data ( since the lower quartile falls above 25% of the data and the upper quartile falls above 75% of the data

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17
Q

Q2

A

median ( 50th percentile)

18
Q

5 N SUMMARY of a distribution

A 
reports its median, quartiles, and extremes ( maximum and minimum)
1. minimum
2. maximum
3. Q3
4. median
5 Q1
19
Q

N

A

The number of data values

20
Q

bar over a symbol

A

find the mean

21
Q

Why is the median considered to be RESISTANT to values

A

because it resist values that are extraordinarily large or small and ignores their distance from the center

22
Q

STANDARD DEVIATION (S)

A

takes into account how far each value is from the mean.

Like the mean the standard deviation is only for symmetric data

23
Q

VARIANCE (s^2)

A

The squared average deviation of individual data value from the mean

24
Q

If data values are far from center ( what happens to the spread)

A

The spread ( IQR and SD) will be large

25
Q

If data values are close center ( what happens to the spread)

A

The spread ( IQR and SD) will be small)

26
Q

What does measures of value tell

A

How well other summaries describe the data

27
Q

When data is skewed what measure of center should be used

A

The median ( spread: IQR)

28
Q

When data is symmetric what measure of center should be used

A

The mean (spread : STD)

29
Q

STEPS TO REPRESENTING Quantitaive DATA

A

1 Make a histogram or stem leaf display

  1. Discuss the center and spread
    a. If the shape is skewed report the median and IQR
    b. If the shape is symmetric report the mean and standard deviation ( for unimodal symmetric data the IQR is usually larger than the standard deviation.
  2. Discuss any unusual features ( modes, outliers)
30
Q

median is paired with

A

IQR

31
Q

mean is paired with

A

standard deviation

32
Q

a Histograms x and axis

A

x axis - the WHAT that was measured

y axis - the COUNT

33
Q

BAR GRAPHS -bars

A

indicate how many cases /counts of categorical data are piled into each category

34
Q

histogram bars

A

represent counts of data piled into intervals of quantitative variable

35
Q

what statistical summaries require the data must be in order

A
  1. median

2 quartiles/percentiles, IQR

36
Q

summary statistics that are resistant to ouliers

A
  1. Median

2. IQR

37
Q

summary statistics that are not resistant to ouliers

used only on symmetric data

A

mean and standard deviation ( they are sensitive to outliers

38
Q

3 things to look at for a histogram

A

1 shape: symmetry, mode, skewed

  1. center
  2. spread
39
Q

MIDRANGE

A

average of the minimum and maximum values

40
Q

RANGE

A

. single value

. maximum-minimum

41
Q

MEASURES OF SPREAD

A

range, IQR,variance , standard deviation

They tell how well other summaries describe the data

Statistics (7 decks)

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