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Chapter 2 • Section 2.1: Organizing qualitative data • Section 2.2: Organizing quantitative data • Section 2.3: skip • Section 2.4: Misrepresentations of data

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Page 1: Chapter 2 Section 2.1: Organizing qualitative data Section 2.2: Organizing quantitative data Section 2.3: skip Section 2.4: Misrepresentations of data

Chapter 2

• Section 2.1: Organizing qualitative data• Section 2.2: Organizing quantitative data• Section 2.3: skip• Section 2.4: Misrepresentations of data

Page 2: Chapter 2 Section 2.1: Organizing qualitative data Section 2.2: Organizing quantitative data Section 2.3: skip Section 2.4: Misrepresentations of data

Qualitative vs. Quantitative (Different tools for different data)

• Question 1: Type of skin cancer– A: Qualitative– B: Quantitative

Page 3: Chapter 2 Section 2.1: Organizing qualitative data Section 2.2: Organizing quantitative data Section 2.3: skip Section 2.4: Misrepresentations of data

Qualitative vs. Quantitative (Different tools for different data)

• Question 1: Type of skin cancer– A: Qualitative– B: Quantitative

• Question 2: Quarterly profit – A: Qualitative– B: Quantitative

Page 4: Chapter 2 Section 2.1: Organizing qualitative data Section 2.2: Organizing quantitative data Section 2.3: skip Section 2.4: Misrepresentations of data

Qualitative vs. Quantitative (Different tools for different data)

• Question 1: Type of skin cancer– A: Qualitative– B: Quantitative

• Question 2: Quarterly profit – A: Qualitative– B: Quantitative

• Question 3: Customer satisfaction– A: Qualitative– B: Quantitative

Page 5: Chapter 2 Section 2.1: Organizing qualitative data Section 2.2: Organizing quantitative data Section 2.3: skip Section 2.4: Misrepresentations of data

Qualitative vs. Quantitative (Different tools for different data)

• Question 1: Type of skin cancer– A: Qualitative– B: Quantitative

• Question 2: Quarterly profit – A: Qualitative– B: Quantitative

• Question 3: Customer satisfaction– A: Qualitative (poor, moderate, high)– B: Quantitative (1,2,3,4,5,6,7,8,9,10)

It isn’t always totally clear!

Page 6: Chapter 2 Section 2.1: Organizing qualitative data Section 2.2: Organizing quantitative data Section 2.3: skip Section 2.4: Misrepresentations of data

• Frequency: A fancy word for “count”

Page 7: Chapter 2 Section 2.1: Organizing qualitative data Section 2.2: Organizing quantitative data Section 2.3: skip Section 2.4: Misrepresentations of data

• Frequency: A fancy word for “count”• Distribution: A way to describe how likely

certain values are to be observed.

Page 8: Chapter 2 Section 2.1: Organizing qualitative data Section 2.2: Organizing quantitative data Section 2.3: skip Section 2.4: Misrepresentations of data

• Frequency: A fancy word for “count”• Distribution: A way to describe how likely

certain values are to be observed.• Frequency distribution: A list tabulating the

number of occurrences for each category

Page 9: Chapter 2 Section 2.1: Organizing qualitative data Section 2.2: Organizing quantitative data Section 2.3: skip Section 2.4: Misrepresentations of data

• Frequency: A fancy word for “count”• Distribution: A way to describe how likely

certain values are to be observed.• Frequency distribution: A list tabulating the

number of occurrences for each category• Relative frequency distribution: A frequency

distribution that uses proportions instead of counts.

Page 10: Chapter 2 Section 2.1: Organizing qualitative data Section 2.2: Organizing quantitative data Section 2.3: skip Section 2.4: Misrepresentations of data

Which is a relative frequency table?Statistics 108 students’ class standings (n=79)

Class standing

Freshmen 0.5000

Sophomore 0.1500

Junior 0.1750

Senior 0.1625

A

B

Page 11: Chapter 2 Section 2.1: Organizing qualitative data Section 2.2: Organizing quantitative data Section 2.3: skip Section 2.4: Misrepresentations of data

SophomoreSeniorJuniorFreshman

50

40

30

20

10

0

Class

Perc

ent

Stat 108 students

Percent within all data.

These graphs are:(A)bar graphs (B)histograms

Which graph is the relative frequency graph? (A) top graph(B) bottom graph

Page 12: Chapter 2 Section 2.1: Organizing qualitative data Section 2.2: Organizing quantitative data Section 2.3: skip Section 2.4: Misrepresentations of data

• The only difference between a frequency bar graph and a relative frequency bar graph is the labeling of the y-axis. (Likewise for histograms.)

• Relative frequency saves the reader calculations

• Frequency graphs tell the reader the actual counts.

Page 13: Chapter 2 Section 2.1: Organizing qualitative data Section 2.2: Organizing quantitative data Section 2.3: skip Section 2.4: Misrepresentations of data

A pie chart of the data

Fr

So

Jr

Sr

Page 14: Chapter 2 Section 2.1: Organizing qualitative data Section 2.2: Organizing quantitative data Section 2.3: skip Section 2.4: Misrepresentations of data

Use the below data to calculate degrees of the sophomore slice.

(A)12 degrees(B)0.15 degrees(C)15 degrees(D)55 degrees

Page 15: Chapter 2 Section 2.1: Organizing qualitative data Section 2.2: Organizing quantitative data Section 2.3: skip Section 2.4: Misrepresentations of data

Histograms

• Histograms are for quantitative data• “Classes” or “bins” are which data are

grouped into.• Upper and lower limit for each class/bin is

subjective.• Goal: Summarize data, but leave some detail.

Page 16: Chapter 2 Section 2.1: Organizing qualitative data Section 2.2: Organizing quantitative data Section 2.3: skip Section 2.4: Misrepresentations of data

Histograms of sparrow weights

Moderate number of bins

Fre

qu

en

cy

22 24 26 28 30 32

01

02

0

lots of bins

Fre

qu

en

cy

22 24 26 28 30 32

05

10

15

Page 17: Chapter 2 Section 2.1: Organizing qualitative data Section 2.2: Organizing quantitative data Section 2.3: skip Section 2.4: Misrepresentations of data

Weights of 87 sparrows (grams)23.2 23.3 23.3 23.5 23.6 23.7 23.8 23.9 24 24.1 24.2 24.3 24.3 24.3 24.4 24.5 24.6 24.6 24.6 24.6 24.7 24.7 24.7 24.8 24.8 24.9 24.9 24.9 25 25 25 25.1 25.4 25.5 25.5 25.6 25.6 25.6 25.7 25.7 25.7 25.7 25.7 25.8 25.9 25.9 26 26 26 26 26 26.1 26.1 26.2 26.2 26.3 26.3 26.4 26.5 26.5 26.5 26.5 26.6 26.6 26.7 26.7 26.7 26.8 26.8 26.9 26.9 26.9 26.9 27 27 27.1 27.3 27.5 27.5 27.6 27.9 28 28.3 28.3 28.6 29 31

Stem-and-leaf plot

In the below software’s stem-and-leaf plot, the decimal point is at the | Displays vary slightly across statistical software

23 | 23356789 24 | 01233345666677788999 25 | 000145566677777899 26 | 000001122334555566777889999 27 | 00135569 28 | 0336 29 | 0 30 | 31 | 0

Page 18: Chapter 2 Section 2.1: Organizing qualitative data Section 2.2: Organizing quantitative data Section 2.3: skip Section 2.4: Misrepresentations of data

Determine the original data set:(The decimal point is 1 digit(s) to the right of the |)

0| 234 0 | 5889 1 | 000134444 1 | 578 2 | 00(A) 0.2, 0.3, 0.4, 0.5, 0.8, 0.8, 0.9, 1, 1, 1, 1.1, 1.3, 1.4, 1.4, 1.4, 1.4, 1.5, 1.7,

1.8, 2, 2 (B) 2, 3, 4, 5, 8, 8, 9, 10, 10, 10, 11, 13, 14, 14, 14, 14, 15, 17, 18, 20, 20(C) 234, 5889, 1000, 1001, 1003, 1004, 1004, 1004, 1004, 1004, 1587, 200(D) 0.234, 0.5889, 1.000134444, 1.578, 2.00

Page 19: Chapter 2 Section 2.1: Organizing qualitative data Section 2.2: Organizing quantitative data Section 2.3: skip Section 2.4: Misrepresentations of data

Create a stem-and-leaf plot for values:24,25,26,29,29,30,31,31,35,36,36

2 | 4 2 | 5699 3 | 011 3 | 566

2 | 45699 3 | 011566

Page 20: Chapter 2 Section 2.1: Organizing qualitative data Section 2.2: Organizing quantitative data Section 2.3: skip Section 2.4: Misrepresentations of data

Dot Plot

Sparrow weights (grams)

Co

un

t

0

5

10

15

20

25

24 26 28 30

Page 21: Chapter 2 Section 2.1: Organizing qualitative data Section 2.2: Organizing quantitative data Section 2.3: skip Section 2.4: Misrepresentations of data

Bad graphs…

Page 22: Chapter 2 Section 2.1: Organizing qualitative data Section 2.2: Organizing quantitative data Section 2.3: skip Section 2.4: Misrepresentations of data
Page 23: Chapter 2 Section 2.1: Organizing qualitative data Section 2.2: Organizing quantitative data Section 2.3: skip Section 2.4: Misrepresentations of data
Page 24: Chapter 2 Section 2.1: Organizing qualitative data Section 2.2: Organizing quantitative data Section 2.3: skip Section 2.4: Misrepresentations of data