Random Excerpts from ECON 310 E-learning Curriculum

 

Description

ECON 310 is designed for students enrolled in the Bachelor of Arts degree program in Administrative Studies. It is an upper-level course in statistics that teaches students how to solve problems in economics and business by applying statistical principles. The topics covered include probability theory, hypothesis testing, sampling methods and estimation, simple and multiple regression and correlation analysis, analysis of variance and time-series and forecasting.

 

Objectives

By the end of this course students should be able to:

§         Calculate probabilities using the rules of addition, rules of multiplication and Bayes’ theorem.

§         Describe the characteristics and compute probabilities using the Binomial, Poisson and Hypergeometric Probability distributions.

§         Distinguish between discrete and continuous random variables.

§         Apply central limit theorem to calculate probabilities in specific populations.

§         Estimate population parameters from sample statistics with appropriate confidence intervals and point estimators.

§         Conduct one, two and matched sample hypothesis definition and testing.

§         Compare the variability between groups with the variability within groups using the one-way and two-way Analysis of Variance.

§         Use simple and multiple regression models to estimate and test for linear relationships between a dependent variable and one or more independent variables.

§         Compute simple and multiple correlation coefficients and test for their significance.

§         Construct and interpret Laspeyres, Paasche, and value price indices.

§         Use a time-series model to identify and calculate trend and seasonal variation.

§         Use trend equations to forecast future time periods and to develop seasonally adjusted forecasts.

§         Practice calculation of selected statistical tests using assigned computer programs and web resources.

The six units in ECON 310 are focused on the following themes:

1.      Probability Theory

2.      Sampling Methods and Estimation

3.      Hypothesis Testing

4.      Analysis of Variance

5.      Simple and Multiple Regression Analysis and Correlation

6.      Time-Series Analysis, Indexing and Forecasting

 

Probability is the foundation of statistical inference where the chance that something will occur in the future is estimated and calculated. In other words, it is the likelihood or chance that a particular event will occur. Inferential statistics involves taking a sample from a population, computing a statistic on the sample, and inferring from the resulting statistic what the value of the corresponding parameter of the population represented by the sample will be. Probability provides the link between describing and presenting information obtained from samples and being able to make inferences to relevant larger populations.

 

v     Rule of Addition – used to compute the probability of the occurrence of a Union of two or more events.

 

 

                        Figure 1.2 Union of Two Events

 

Factorials are a shorthand way to reduce the amount of numeric notation in counting,  basically indicating how many different ways an item can be sequenced. For instance:

 

6! = 6 x 5 x 4 x 3 x 2  x 1 = 720

5! = 5 x 4 x 3 x 2 x 1 = 120

4! = 4 x 3 x 2 x 1 = 24

3! = 3 x 2 x 1 = 6

2! = 2 x 1 = 2

1! = 1

0! = 1

 

 

EXCEL GUIDE: Two Sample T Test for Independent Samples

 

The following will perform a hypothesis test for the difference of population means.

 

v     Click Tools > Data Analysis

v     In the window titled Data Analysis select t-Test: Two-Samples Assuming Equal Variances and click OK.

v     A new window titled t-Test: Two-Samples Assuming Equal Variances should now appear. This window has many options. Below is a brief explanation of each:

 

§         Highlight the data from the 1st sample and put into Variable 1 Range

§         Highlight the data from the 2nd sample and put into Variable 2 Range

§         Hypothesized Mean Difference: is obtained from the null hypothesis. (i.e. Ho : 1 - 2 = Hypothesized Mean Difference )

§         Labels is used if the variable names were included under Variable Range

§         Alpha: is the level of significance for the test.

 

v     You must select one of the following Output options:

 

·        Click Output Range if you want the test results to be placed on the current sheet. Next, simply input the cell where you want the output to be placed.

·        Click New Worksheet Ply if you want the test results to be placed on a new sheet. Next, type the name of the new sheet where you want the output to be placed.

·        Click OK. The test results should be placed onto your spreadsheet.