Course Information Package
|Course Unit Title||STATISTICS II|
|Course Unit Code||AMAT210|
|Course Unit Details||BA Business Administration (DL) (Compulsory courses) - BA Business Administration (Required Courses) - BSc Marketing with Digital Technologies (Required modules) - BA Accounting and Finance (Required Courses) - BSc Maritime Studies (Business and Maritime Electives) -|
|Number of ECTS credits allocated||5|
|Learning Outcomes of the course unit||By the end of the course, the students should be able to:|
|Mode of Delivery||Face-to-face|
|Recommended optional program components||NONE|
Sampling and sampling distributions
The various kinds of sampling techniques (simple, stratified, clustering). Sampling from finite and infinite population. Sampling distribution of the mean.
Recall of the normal distribution. Point estimation of the population mean. Interval estimation of the population mean for large sample with s known and s unknown. The t-distribution and the table of t-distribution. Interval estimations of the population mean for small sample with s known or s unknown. Interval estimation of the population proportion. Determining the sample size for estimating mean or proportion.
Hypothesis testing. Null and alternative hypothesis. Significant level. Types or errors (type I and II).
Tests of goodness of fit and independence
Chi-square distribution and its table. Chi square goodness of fit test. Contingency tables and the chi square test of association. “Statistical significance”.
Independent and dependent variables. Pearson’s coefficient and the values of it
Simple linear regressionIndependent and dependent variable. Scatter diagram. Coefficients (b0 and b1) of the simple linear regression model. Regression, using data from the business environment. Forecasting.
|Recommended and/or required reading:|
|Planned learning activities and teaching methods|
The taught part of course is delivered to the students by means of lectures, and tutorials. Lecture notes are available through the e-learning platform of the University, and the instructor’s webpage. Students are encouraged for class work, problem solving and discussion. Students are also introduced in data analysis using IBM SPSS but under a different course (ARRW101).
|Assessment methods and criteria|
|Language of instruction||English|