Principles of Statistics

Source:国际学院 Date:2013-12-30 Hits:75

Objectives:

Statistics is a very important course, which is concerned about making quantitative analysis for the social and economic phenomena, or other fields, and uses mathematic model to describe the relationship between economic variables and other variables which have a random feature. It is the core course in the economics and business. Through this course, students are required to understand the role of statistics in the modern economics and the characteristic of statistics, understand its importance in the real economic life, master the basic thought of statistics, and the principle of statistics, master the procedure of the application of statistics, be able to analyze economic problem based on the statistics’ tools, get a good base for the further study in economics and business.

Requirements:

During the lecture, the teachers should emphasize the economic theory and the analysis for the economic phenomena, and pay more attention to give lectures about the basic thought of the statistics, and should avoid the complex proof on the mathematics, but it is necessary for some basic proofs about the basic principle in statistics, so the basic knowledge on the mathematics should be emphasized. At last, we should make summaries for the concepts and the application for statistics

Contents:

In the first chapter, students should know what is meant by statistics,why study statistics, types of statistics, levels of measurement.

In the second chapter, students should know how to constructing a frequency distribution, what is relative frequency distribution, what is a frequency distribution, what is a histogram, what is a frequency Polygon and other graphic presentations of data and how to construct them

In the third chapter, students should know what is the population mean, and what is the sample mean, the properties of the arithmetic mean, what is the weighted mean, the meaning of the median and the mode, what is the geometric mean, and how to calculate them, know how to use them according to various conditions, know the relative positions of the mean, median, mode.

In the fourth chapter, students should know why study dispersion? What measures can be used to describe dispersion, the meaning of range, mean deviation, variance and standard deviation, how to explain and use the standard deviation, know the Chebyshev’s Theorem and the empirical rule

In the fifth chapter, students should know what is a probability, approaches to probability, the meaning of Classical Probability, .Empirical Concept, and Subjective Probability, learn some rules of probability, learn rules of addition and rules of multiplication, learn how to use them in the application.

In the sixth chapter, students should know what is a probability distribution, the meaning of random variables, what is a discrete random variable and what is a continuous random variable, know the definition of the mean, variance, and standard deviation of a probability distribution, and how to calculate them.

In the seventh chapter, students should know what is a normal probability distribution, the family of normal distribution, the meaning of the standard normal, how to calculate areas under the normal curve and find areas under the normal curve, and find the probability of a normal variable being less than a particular value.

In the eighth chapter, students should know how to sample the population, the types of probability sampling methods: 1. Simple random sampling, 2.Systematic random sampling, 3.Stratified random sampling, 4.Cluster sampling, know the features of these probability sampling methods, know the meaning of the sampling “error”, the meaning of sampling distribution of the sample mean, the essence of the central limit theorem, and how to use the sampling distribution of the sample mean to make a estimate about a mean.

In the nineth chapter, students should know the meaning of point estimates and confidence intervals, know how to construct a confidence interval for a mean in different situations, how to construct confidence interval for a proportion, the meaning of finite-population correction factor, how to choose an appropriate sample size.

In the tenth chapter, students should know what is a hypothesis? What is hypothesis testing, Five-step procedure for testing a hypothesis; the meaning of one-tailed and two-tailed tests of significance, the meaning of p-value in hypothesis testing, how to test for a population mean: large sample, population standard deviation unkown, test for a population mean: small sample, population standard deviation unkown, testing concerning proportions.

In the eleventh chapter, students should know how to test two-sample means tests of hypothesis and test about proportions for two populations.

In the twelfth chapter, students should know what is correlation analysis, the meaning of the coefficient of correlation, the meaning of the coefficient of determination, how to test the significance of the correlation coefficient, what is a regression analysis, the meaning of least squares principle, the meaning of the standard error of estimate, and the assumptions underlying linear regression, how to make confidence intervals and prediction intervals.

In the thirteenth chapter, students should know what is a simple index numbers, Why convert data to indexes, how to construct an index numbers the meaning of unweighted indexes and the meaning of weighted indexes, know how to calculate laspeyres’price index, paasche’s price index, and fisher’s ideal index, the meaning of value index.

Credits: 3