Transcript Introduction to Statistics

Introduction to
Statistics
Mr. Joseph Najuch
Introduction to statistical concepts including
descriptive statistics, basic probability rules,
conditional probability, probability distributions,
estimation of parameters, hypothesis testing using
one or two samples, correlation and regression.
Computer applications and simulations are done
using MS EXCEL and TI-84 Graphing Calculators.
1
In your own words…..
•Define what you
believe statistics
means…
2
Why study statistics?
Understanding statistics will……
Provide tools to analyze media reports
- Presidential approval rating
Help make investment decisions
- 1 year vs. 5 year performance
Conduct research on major purchases
- Consumer Reports on Dyson vacuum
 Do your own research and make
conclusions
3
"Who do you think has the better ideas for
strengthening the nation's economy:
Barack Obama or John McCain?"
-
Obama 45%
McCain 28%
Both Equally 8%
Neither 11%
Unsure 8%
Info from:
Los Angeles Times/Bloomberg Poll.
Aug. 15-18, 2008. N=1,248 registered
voters nationwide.
MoE ± 3.
4
Definitions
• Statistics – is the science of collecting,
organizing, summarizing, and analyzing
information to draw conclusions or answer
questions.
• Data – are a fact or information coming
from observations or counts, used to draw a
conclusion or make a decision. It can be
numerical or non-numerical.
5
Definitions
• Population – the group being studied (N)
• Sample – a subset of the population (n)
• Descriptive Statistics – organizing and
summarizing the information collected
(describe information in the form of charts, graphs, ect.)
• Inferential statistics – takes the results from
the sample and extends to the whole
population
6
Definitions
Qualitative Data: Deals with descriptions.
• Data can be observed but not measured.
• Colors, textures, smells, tastes, appearance, beauty, etc.
• Qualitative → Quality
Quantitative Data: Deals with numbers.
• Data which can be measured.
• Length, height, area, volume, weight, speed, time,
temperature, humidity, sound levels, cost, members, ages,
• Quantitative → Quantity
7
Univariate Data
Bivariate Data
Involving a single variable
Involving two variables
- Does not deal with causes or
relationships
-Deals with causes or relationships
The major purpose of univariate
analysis is to describe stats.
The major purpose of bivariate analysis
is to explain the reason for the results.
*central tendency - mean, mode, median
*dispersion - range, variance, max, min,
*quartiles, standard deviation. frequency
*distributions bar graph, histogram, pie
chart, line graph, box-and-whisker plot
*analysis of two variables
*simultaneously correlations
comparisons, relationships, causes,
explanations
*tables where one variable is contingent
on the values of the other variable.
*independent and dependent variables
Sample question: How many of the
students in the freshman class are
female?
Sample question: Is there a
relationship between the number of
females in Computer Programming and
their scores in Mathematics?
Data Classification (Types)
There are four Levels of Measurement:
Nominal
Ordinal
Interval
Ratio
* Be sure to understand the difference
between each. (p. 14)