Chapter 1

The Role of Statistics and the

Data Analysis Process

What is statistics?

•the science of collecting, analyzing, and drawing conclusions from data

Why should one study statistics?

1. To be informed . . .a) Extract information from tables,

charts and graphsb) Follow numerical argumentsc) Understand the basics of how data

should be gathered, summarized, and analyzed to draw statistical conclusions

Can dogs help patients with heart failure by reducing stress and anxiety?When people

take a vacation do they really

leave work behind?

Why should one study statistics? (continued)2.To make informed judgments

3.To evaluate decisions that affect your life

If you choose a particular major, what are your chances of finding a job when you

graduate?

Many companies now require drug screening as a condition of employment. With these

screening tests there is a risk of a false-positive reading. Is

the risk of a false result acceptable?

What is variability?

Suppose you went into a convenience store to purchase a soft drink. Does every can on the shelf contain exactly 12 ounces?

NO – there may be a little more or less in the various cans due to the variability that is inherent in the filling process.

In fact, variability is almost universal!universal!

It is variability that makes life

interesting!!

If the Shoe Fits ...

The two histograms to the right display the distribution of heights of gymnasts and the distribution of heights of female basketball players. Which is which? Why?

Heights – Figure A

Heights – Figure B

If the Shoe Fits ...

Suppose you found a pair of size 6 shoes left outside the locker room. Which team would you go to first to find the owner of the shoes? Why?

Suppose a tall woman (5 ft 11 in) tells you see is looking for her sister who is practicing with a gym. To which team would you send her? Why?

The Data Analysis Process1. Understand the nature of the

problem

2. Decide what to measure and how to measure it

3. Collect data

4. Summarize data and perform preliminary analysis

5. Perform formal analysis

6. Interpret results

It is important to have a clear direction before

gathering data.It is important to carefully define the variables to be studied and to develop appropriate methods for determining their values.

It is important to understand how data is collected because the type of analysis that is appropriate depends on how the data was collected!

This initial analysis provides insight into important

characteristics of the data.

It is important to select and apply the appropriate inferential statistical

methodsThis step often leads to the formulation of new research

questions.

Suppose we wanted to know the average GPA of high school graduates in the nation this year.

We could collect data from all high schools in the nation. What term would be used to

describe “all high school graduates”?

Population

• The entire collection of individuals or objects about which information is desired

• A census is performed to gather about the entire population

What do you call it when you collect data

about the entire population?

GPA Continued:Suppose we wanted to know the average GPA of high school graduates in the nation this year.

We could collect data from all high schools in the nation.

Why might we not want to use a census here?

If we didn’t perform a census, what would we

do?

Sample

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

What would a sample of all high school graduates across the nation look like?High school graduates from each state (region), ethnicity, gender, etc.

GPA Continued:Suppose we wanted to know the average GPA of high school graduates in the nation this year.

We could collect data from a sample of high schools in the nation.

Once we have collected the data, what would we do

with it?

Descriptive statistics•the methods of organizing & summarizing data

• Create a graph

If the sample of high school GPAs contained 1,000 numbers, how could the data be organized or summarized?

• State the range of GPAs• Calculate the average GPA

GPA Continued:Suppose we wanted to know the average GPA of high school graduates in the nation this year.

We could collect data from a sample of high schools in the nation.

Could we use the data from our sample to answer this

question?

Inferential statistics•involves making generalizations from a sample to a populationBased on the sample, if the average GPA for high school graduates was 3.0, what generalization could be made?

The average national GPA for this year’s high school graduate is approximately 3.0.Could someone claim that the average

GPA for graduates in your local school district is 3.0?No. Generalizations based on the results of a sample can only be made back to the population from which the sample came from.

Be sure to sample from the population of

interest!!

Until Tomorrow……….

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

•Suppose we wanted to know the average GPA of high school graduates in the nation this year. Define the variable of interest.The variable of interest is the GPA of high school graduates

Is this a variable . . .The number of wrecks per week at the intersection

outside school? YES

Data

•The values for a variable from individual observations

For this variable . . .The number of wrecks per week at the intersection outside . . . What could observations be? 0, 1, 2,

…

Two types of variables

categorical

numerical

discrete continuous

Categorical variables

•Qualitative

•Identifies basic differentiating characteristics of the populationCan you name any

categorical variables?

Numerical variables•quantitative

•observations or measurements take on numerical values

•makes sense to average these values

•two types - discrete & continuous

Can you name any numerical variables?

Discrete (numerical)

•Isolated points along a number line

•usually counts of items

Continuous (numerical)•Variable that can be any value in a given interval

•usually measurements of something

Identify the following variables:1. the color of cars in the teacher’s

lot

2. the number of calculators owned by students at your school

3. the zip code of an individual

4. the amount of time it takes students to drive to school

5. the appraised value of homes in your city

Categorical

Categorical

discrete numerical

Discrete numerical

Continuous numerical

Is money a measurement or a count?

Classifying variables by the number of variables in a

data setSuppose that the PE coach records the height of each student in his class.

Univariate - data that describes a single characteristic of the population

This is an example of a univariate data

Classifying variables by the number of variables in a

data setSuppose that the PE coach records the height and weight of each student in his class.

Bivariate - data that describes two characteristics of the population

This is an example of a bivariate data

Classifying variables by the number of variables in a

data setSuppose that the PE coach records the height, weight, number of sit-ups, and number of push-ups for each student in his class.

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

This is an example of a multivariate data

Bar ChartWhen to Use Categorical data

How to construct– Draw a horizontal line; write the categories or labels below the line at regularly spaced intervals

– Draw a vertical line; label the scale using frequency or relative frequency

– Place equal-width rectangular bars above each category label with a height determined by its frequency or relative frequency

Bar Chart (continued)What to Look For Frequently or infrequently occurring categories

Collect the following data and then display the data in a bar chart:

What is your favorite ice cream flavor?

Vanilla, chocolate, strawberry, or other

Dotplot

When to Use Small numerical data sets

How to construct– Draw a horizontal line and mark it with an appropriate numerical scale

– Locate each value in the data set along the scale and represent it by a dot. If there are two are more observations with the same value, stack the dots vertically

Dotplot (continued)

What to Look For – The representative or typical value– The extent to which the data values spread out– The nature of the distribution along the number line

– The presence of unusual values

Collect the following data and then display the data in a dotplot:

How many body piercings do you have?