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Page 1: Chapter 1 & 3. Statistics 4 the science of collecting, analyzing, and drawing conclusions from data

Chapter 1 & 3

Page 2: Chapter 1 & 3. Statistics 4 the science of collecting, analyzing, and drawing conclusions from data

Statisticsthe science of collecting, analyzing, and drawing conclusions from data

Page 3: Chapter 1 & 3. Statistics 4 the science of collecting, analyzing, and drawing conclusions from data

Descriptive statisticsthe methods of organizing & summarizing data

Page 4: Chapter 1 & 3. Statistics 4 the science of collecting, analyzing, and drawing conclusions from data

Inferential statisticsinvolves making generalizations from a sample to a population

Page 5: Chapter 1 & 3. Statistics 4 the science of collecting, analyzing, and drawing conclusions from data

PopulationThe entire collection of individuals or objects about which information is desired

Page 6: Chapter 1 & 3. Statistics 4 the science of collecting, analyzing, and drawing conclusions from data

SampleA subset of the population, selected for study in some prescribed manner

Page 7: Chapter 1 & 3. Statistics 4 the science of collecting, analyzing, and drawing conclusions from data

Variable any characteristic whose value may change from one individual to another

Page 8: Chapter 1 & 3. Statistics 4 the science of collecting, analyzing, and drawing conclusions from data

Dataobservations on single variable or simultaneously on two or more variables

Page 9: Chapter 1 & 3. Statistics 4 the science of collecting, analyzing, and drawing conclusions from data

Types of variables

Page 10: Chapter 1 & 3. Statistics 4 the science of collecting, analyzing, and drawing conclusions from data

Categorical variablesor qualitativeidentifies basic

differentiating characteristics of the population

Page 11: Chapter 1 & 3. Statistics 4 the science of collecting, analyzing, and drawing conclusions from data

Numerical variablesor quantitative observations or measurements

take on numerical valuesmakes sense to average these

valuestwo types - discrete & continuous

Page 12: Chapter 1 & 3. Statistics 4 the science of collecting, analyzing, and drawing conclusions from data

Discrete (numerical)

listable set of valuesusually counts of items

Page 13: Chapter 1 & 3. Statistics 4 the science of collecting, analyzing, and drawing conclusions from data

Continuous (numerical)

data can take on any values in the domain of the variable

usually measurements of something

Page 14: Chapter 1 & 3. Statistics 4 the science of collecting, analyzing, and drawing conclusions from data

Classification by the number of variablesUnivariate - data that describes a single

characteristic of the population

Bivariate - data that describes two characteristics of the population

Multivariate - data that describes more than two characteristics (beyond the scope of this course

Page 15: Chapter 1 & 3. Statistics 4 the science of collecting, analyzing, and drawing conclusions from data

Identify the following variables:1. the income of adults in your city

2. the color of M&M candies selected at random from a bag

3. the number of speeding tickets each student in AP Statistics has received

4. the area code of an individual

5. the birth weights of female babies born at a large hospital over the course of a year

Numerical

Numerical

Numerical

Categorical

Categorical

Page 16: Chapter 1 & 3. Statistics 4 the science of collecting, analyzing, and drawing conclusions from data

Graphs for categorical data

Page 17: Chapter 1 & 3. Statistics 4 the science of collecting, analyzing, and drawing conclusions from data

Bar Graph

Used for categorical data Bars do not touch Categorical variable is typically on the horizontal

axis To describe – comment on which occurred the

most often or least often May make a double bar graph or segmented bar

graph for bivariate categorical data sets

Page 18: Chapter 1 & 3. Statistics 4 the science of collecting, analyzing, and drawing conclusions from data

Using class survey data:

graph birth month

graph gender & handedness

Page 19: Chapter 1 & 3. Statistics 4 the science of collecting, analyzing, and drawing conclusions from data

Pie (Circle) graph

Used for categorical data To make:

– Proportion 360°

– Using a protractor, mark off each part

To describe – comment on which occurred the most often or least often

Page 20: Chapter 1 & 3. Statistics 4 the science of collecting, analyzing, and drawing conclusions from data

Graphs for numerical data

Page 21: Chapter 1 & 3. Statistics 4 the science of collecting, analyzing, and drawing conclusions from data

Dotplot

Used with numerical data (either discrete or continuous)

Made by putting dots (or X’s) on a number line

Can make comparative dotplots by using the same axis for multiple groups

Page 22: Chapter 1 & 3. Statistics 4 the science of collecting, analyzing, and drawing conclusions from data

Distribution Activity . . .

Page 23: Chapter 1 & 3. Statistics 4 the science of collecting, analyzing, and drawing conclusions from data

Types (shapes)of Distributions

Page 24: Chapter 1 & 3. Statistics 4 the science of collecting, analyzing, and drawing conclusions from data

Symmetricalrefers to data in which both sides are

(more or less) the same when the graph is folded vertically down the middle

bell-shaped is a special type

–has a center mound with two sloping tails

Page 25: Chapter 1 & 3. Statistics 4 the science of collecting, analyzing, and drawing conclusions from data

Uniformrefers to data in which every

class has equal or approximately equal frequency

Page 26: Chapter 1 & 3. Statistics 4 the science of collecting, analyzing, and drawing conclusions from data

Skewed (left or right)refers to data in which one

side (tail) is longer than the other side

the direction of skewness is on the side of the longer tail

Page 27: Chapter 1 & 3. Statistics 4 the science of collecting, analyzing, and drawing conclusions from data

Bimodal (multi-modal)refers to data in which two

(or more) classes have the largest frequency & are separated by at least one other class

Page 28: Chapter 1 & 3. Statistics 4 the science of collecting, analyzing, and drawing conclusions from data

How to describe a numerical,

univariate graph

Page 29: Chapter 1 & 3. Statistics 4 the science of collecting, analyzing, and drawing conclusions from data

What strikes you as the most distinctive difference among the distributions of exam scores in classes A, B, & C ?

Page 30: Chapter 1 & 3. Statistics 4 the science of collecting, analyzing, and drawing conclusions from data

1. Centerdiscuss where the middle of

the data fallsthree types of central

tendency–mean, median, & mode

Page 31: Chapter 1 & 3. Statistics 4 the science of collecting, analyzing, and drawing conclusions from data

What strikes you as the most distinctive difference among the distributions of scores in

classes D, E, & F? Class

Page 32: Chapter 1 & 3. Statistics 4 the science of collecting, analyzing, and drawing conclusions from data

2. Spreaddiscuss how spread out the data

isrefers to the variability of the

data–Range, standard deviation, IQR

Page 33: Chapter 1 & 3. Statistics 4 the science of collecting, analyzing, and drawing conclusions from data

What strikes you as the most distinctive difference among the distributions of exam scores in classes G, H, & I ?

Page 34: Chapter 1 & 3. Statistics 4 the science of collecting, analyzing, and drawing conclusions from data

3. Shaperefers to the overall shape of

the distributionsymmetrical, uniform,

skewed, or bimodal

Page 35: Chapter 1 & 3. Statistics 4 the science of collecting, analyzing, and drawing conclusions from data

What strikes you as the most distinctive difference among the distributions of exam scores in class K ?

K

Page 36: Chapter 1 & 3. Statistics 4 the science of collecting, analyzing, and drawing conclusions from data

4. Unusual occurrencesoutliers - value that lies away

from the rest of the datagapsclustersanything else unusual

Page 37: Chapter 1 & 3. Statistics 4 the science of collecting, analyzing, and drawing conclusions from data

5. In contextYou must write your answer

in reference to the specifics in the problem, using correct statistical vocabulary and using complete sentences!

Page 38: Chapter 1 & 3. Statistics 4 the science of collecting, analyzing, and drawing conclusions from data

More graphs for numerical data

Page 39: Chapter 1 & 3. Statistics 4 the science of collecting, analyzing, and drawing conclusions from data

Stemplots (stem & leaf plots)

Used with univariate, numerical data Must have key so that we know how to read

numbers Can split stems when you have long list of

leaves Can have a comparative stemplot with two

groups

Would a stemplot be a good graph for the number of pieces of gun chewed per day by

AP Stat students? Why or why not?

Would a stemplot be a good graph for the number of pairs of shoes owned by AP Stat

students? Why or why not?

Page 40: Chapter 1 & 3. Statistics 4 the science of collecting, analyzing, and drawing conclusions from data

Example:

The following data are price per ounce for various brands of dandruff shampoo at a local grocery store.

0.32 0.21 0.29 0.54 0.17 0.28 0.36 0.23

Can you make a stemplot with this data?

Page 41: Chapter 1 & 3. Statistics 4 the science of collecting, analyzing, and drawing conclusions from data

Example: Tobacco use in G-rated Movies

Total tobacco exposure time (in seconds) for Disney movies:223 176 548 37 158 51 299 37 11 165 74 9 2 6 23 206 9

Total tobacco exposure time (in seconds) for other studios’ movies:205 162 6 1 117 5 91 155 24 55 17

Make a comparative stemplot.

Page 42: Chapter 1 & 3. Statistics 4 the science of collecting, analyzing, and drawing conclusions from data

Histograms

Used with numerical data Bars touch on histograms Two types

– Discrete• Bars are centered over discrete values

– Continuous• Bars cover a class (interval) of values

For comparative histograms – use two separate graphs with the same scale on the horizontal axis

Would a histogram be a good graph for the fastest speed driven by AP Stat students?

Why or why not?

Would a histogram be a good graph for the number of pieces of gun chewed per day by

AP Stat students? Why or why not?

Page 43: Chapter 1 & 3. Statistics 4 the science of collecting, analyzing, and drawing conclusions from data

Cumulative Relative Frequency Plot(Ogive)

. . . is used to answer questions about percentiles. Percentiles are the percent of individuals that are

at or below a certain value. Quartiles are located every 25% of the data. The

first quartile (Q1) is the 25th percentile, while the third quartile (Q3) is the 75th percentile. What is the special name for Q2?

Interquartile Range (IQR) is the range of the middle half (50%) of the data.

IQR = Q3 – Q1