This chapter introduces key concepts in probability and statistics. It discusses descriptive statistics, which organize and summarize data through numerical summaries and graphs, and inferential statistics, which draw conclusions about populations from samples. Key terms are defined, including population, sample, parameter, statistic, variable, and data. Qualitative and quantitative data are described, with quantitative data further divided into discrete and continuous variables. Examples are provided to illustrate these concepts.

1. Chapter 1
S A M P L I N G A N D D A TA

2. Probability
P r o b ab i l i t y i s t h e m a t h e m a t i c a l t o o l u s e d t o s t u d y
randomness.

3. Statistics
Statistics is the science of
c o l l e c t i n g, o r g a n i z i n g, s u m m a r i z i n g, a n d a n a l y z i n g
d a t a t o d r aw c o n c l u s i o n s o r a n swe r q u e s t i o n s .
I n a d d i t i o n , s t a t i s t i c s i s ab o u t p r ov i d i n g a m e a s u r e
o f c o n f i d e n c e i n a ny c o n c l u s i o n s .

4. 1.2 Statistics
 Descriptive Statistics consist of organizing and summarizing
data through numerical summaries, tables, and graphs.
 Inferential Statistics uses methods for drawing conclusions
and determining how reliable they may be.

5. Do not look in your bag!
GROUP WORK 1. Break into pairs.
2. One person should select four pieces
of twine (one at a time, returning each
piece before selecting the next). The
other person should record the length of
each piece and then calculate the average
of the lengths. You should then switch
jobs and repeat the process.

6. 1.4 Key Terms
 The entire group to be studied is called the popultion.
 For large populations a subset of the population called a
sample is selected and studied.
 A statistics is a numerical summary of a sample.
 A parameter is a numerical summary of a population.
 A statistic can give us an estimate of a parameter or allow us
to test the validity of an established parameter.

7. 1.4 Key Terms
 Goal: A representative sample, one in which the relevant
characteristics of the sample match those of the population.
 A study suffers from bias if its design or conduct tends to
favor certain results.

8. 1.4 Key Terms


9. 1.4 Key Terms
 A variable, often represented by X or Y is a characteristic of
interest of the individuals in the sample.
 Data are the actual values of the variable, often represented
by x or y.

10. The Whatcom County Parks Department is
EXAMPLE considering two possible locations for a new
leash free area where people can bring their
Identify each of the
following: dogs. To find out which location would be
more popular, a survey is taken throughout
Population
one day at Petsmart in which dog owners are
Sample asked which they would be more likely use.
Parameter
Statistic
Variable
Data

11. 1.5 Data
Most variables can be classified as either qualitative or
quantitative
 Qualitative variables allow for classification of individuals
based on some attribute or characteristic.
 Quantitative variables provide numerical measures of
individuals. Arithmetic operations can be performed on the
values of quantitative variables and will provide meaningful
results.

12. 1.5 Data
We can further classify quantitative data as discrete or
continuous.
 A discrete variable is the result of counting.
 A continuous variable is the result of measurement.

13. 1. The number of pairs of shoes you own
GROUP WORK 2. The type of car you drive.
Determine the 3. Where you go on vacation.
correct data type: 4. The distance from your home to the nearest
grocery store.
Qualitative
5. The number of classes you take per school
Quantitative year.
(discrete)
6. The tuition for your classes.
Quantitative 7. The type of calculator you use.
(continuous) 8. Movie ratings.
9. Political party preferences.
10. Weight of sumo wrestlers.
11. Number of correct answers on a quiz.
12. People’s attitude towards the government

14. HOMEWORK
Fill out student questionnaire (due tomorrow)
Read Chapter 1
1.12 #s 1 (only i), 4-11