Economics | Statistical Analysis for Business and Economics (3cr.)
E370 | 1727 | Camp

Economics ,  Statistical Analysis for Business and Economics
E370 ,  1727 & 1740 ,  Camp

E370  Statistical Analysis for Business and Economics

ATTENTION:  More details about this course are available at the
Economics Department Internet site for E370 at the  following address:

This class includes two components: (i) the lectures where statistical
concepts and methods are introduced and discussed, and (ii) computer
labs (recitation sections) where you learn to apply statistical
methods of data analysis using a standard computer package.

Prerequisites:  M118 (Finite Mathematics) completed prior to this
class is an absolute requirement.  At least concurrent registration in
a calculus class (the M119 level or above) is also required.

Required Computer Program:  Microsoft Excel
This program is available through the Windows menu in any of the UITS
clusters.  Statistical applications of EXCEL will be used in this
class.  The knowledge of these EXCEL applications will be required for
exams, quizzes and homework assignments.

Other Requirements:  DOS formatted 3.5 inch floppy disk.

Getting Help:  An extensive (free) tutoring help in this class will be
provided by the Economics Department.  Specific schedule will be
announced in the second week of classes.
Course Objectives
This class builds on your overall quantitative concepts and skills, as
well as on the knowledge of basic probability and statistics you
obtained in your Finite Math class.  This class should substantially
enhance this very important component of your college education.  It
will provide
- the understanding of key statistical concepts used in economics and
- the knowledge of basic statistical methods of data analysis which
are rigorously founded in the theory of probability, and    the
ability to apply these methods with the help of statistical tools
available on computer;
- the ability to draw statistical inferences, i.e., to interpret the
results obtained from the application of statistical methods.

Course Grading
The course grade will be based on the scores you earn for
(i) mid-term exams and the Departmental Final Exam consisting of
multiple choice questions, and
(ii) Evaluation of your computer lab work which will include
-  computer lab tests and assignments using statistical applications
in Microsoft Excel
-  homework assignments which will be given to you in your recitation
(computer lab) section;
- computer lab attendance/participation

I.  Statistics and Measurement
A.      Statistical Problems. Population and Sample Data
B.      Representation of Data: Frequency Distributions and Histograms
C.      Measures of Central Tendency and Dispersion
EXCEL applications: By the end of this section students should be able
to use alternative methods and measures to describe sets of data.
Students should be able to enter data, do calculations of descriptive
statistics and draw histograms both using a calculator and EXCEL
program on computer, and interpret results from a computer printout.

II.  Basic Rules of Probability
A brief review, knowledge presumed within the scope of M118.  An
important concept to review:  independent random events.

III.  Random Variables, Expected Values
A.      Random Variables (brief review, knowledge presumed within the
scope of M118)
B.      Expected Values with the emphasis on finance applications
1.      Mean of a random variable, mean of a sum of random
2.      Variance of a random variable, variance of a sum of
random variables
3.      Covariance

IV.  Probability Distributions
A.      Discrete:       Binomial;
Hypergeometric, Poisson (only the awareness of
the concepts and applicability)
B.      Continuous:     Uniform, Normal and Standard Normal
Student-t  distribution mentioned, more
details postponed until its application in
interval estimation and hypothesis testing
EXCEL applications: By the end of this section students should be able
to identify various probability distributions studied and to use EXCEL
in probability calculations for binomial and normal distribution.

V.  Sampling Distribution and Estimation
A.      Sampling
B.      Sampling distribution of sample mean and proportion, Central
Limit Theorem
C.      Point and Interval Estimation of a Population Mean;
D.      Point and Interval Estimation of a Population Proportion
EXCEL applications: By the end of this section students should be able
to use EXCEL for determining confidence intervals, and to fully
interpret the information in the EXCEL printout regarding sampling
distribution and confidence intervals. They should identify the
applications requiring probability calculations with  z or t
distributions, and to use EXCEL for it.

VI.  Hypothesis Testing
A.      Testing Concepts and Procedures
B.      Testing a Population Mean (z- and t-tests)
C.      Testing a Population Proportion
D.      Chi-Square test of Independence (tentative, time permitting)
EXCEL applications:  By the end of this section students should be
able to use sample data to test claims and propositions about
population parameters.  They should be able to use EXCEL to calculate
critical values and p-values (using normal, t- and Chi-Square
distributions where appropriate), and to apply them in making an

VII.  Regression and Correlation
A.      A Simple Linear Regression Model
B.      The Method of Least Squares
1.      Parameter estimation
2.      Regression, total and error sum of squares
3.      Parameter variance estimation
4.      Predicting a particular value for   y  for a given
value of   x
C.      Inference concerning the slope and intercept
D.      Correlation, goodness of fit
EXCEL applications:  Given paired data on dependent variable y and
independent variable x, students should be able to apply EXCEL to
obtain least squares estimation of the linear relationship between
these two variables, to predict values of y given the values of x,
based on the simple linear regression model, to test hypotheses about
the coefficients of the model.  Given the EXCEL printout, they will be
expected to identify and to interpret coefficients of regression model
and other statistics.

VIII.  Multiple Regression
A.      Linear Regression Model
B.      The Method of Least Squares in a Multiple Regression Model
C.      Predicting with a Multiple Regression Model
D.      Testing hypotheses about coefficients of a model
E.      R-squared measure of the goodness of fit of a model
EXCEL applications:  Students will be expected to interpret EXCEL
printouts of least squares estimation of a linear relationship between
a dependent variable and several independent variables, to make
predictions about dependent variable based on the model, and to test
hypotheses about its coefficients.