1 Economics 240A Power One Outline Course Organization Course Overview Resources for Studying 2 Organization Cont Takehome Project An exercise to test your quantitative and writing skills You can work collectively but the 2 3 page report must be yours Last Fall we did group projects with PowerPoint presentations and I will probably repeat this format Your grade for the course will be based on your scores on the midterm 18 final 37 and 2 projects each 18 and your effort as indicated by problem sets and lab exercises turned in for credit 9 Of course the latter are more important than the weight indicated I distribute the grades by letter weighing the problem sets one third of a grade point and by total score for the class and reconcile the course grades Course Overview Topics in Statistics Descriptive Statistics Exploratory Data Analysis Probability and Distributions Proportions Interval Estimation Hypothesis Testing Correlation and Regression Analysis of Variance 5 Concepts 1 Two types of data Time series Cross section 6 http research stlouisfed org fred2 7 http research stlouisfed org fred2 8 9 10 Examples of 1 Graphical Display of Results 2 Cross Section Data 3 Survey Sample of 12 571 1 Men women 2 Ages 15 44 11 What is the Message 12 Concepts 2 Population Versus Sample Mid Tem Elections this Fall Population All eligible voters Sample Field poll sample Pop 13 Concepts 3 Different views of the world universe Deterministic Stochastic 14 Statistical Inference and Probability Deterministic Newtonian physics e g distance rate time Einsteinian relativistic physics E m c2 Stochastic random Quantum mechanics 15 Statistical Inference and Probability Probability A tool to understand chance What is chancy about the statistical world we will study Example Suppose I number everyone in the class from 1 to 30 And draw one number a meeting to ask a question what is the likelihood I will call on you today 16 17 18 19 20 Resources for Studying Keller Text Readings CDROM Applets Instructor Lecture Notes Lab Notes Exercises Problem Sets PowerPoint Slide Shows 21 http econ ucsb edu 22 Keller CDROM 23 http www duxbury com statistics 24 Student Book Companion Siten 25 Concepts 4 Three types of data Cardinal Ordinal Categorical 26 Keller Warrack Slide Show Excerpts from Ch 2 27 Chapter 2 Graphical Descriptive Techniques 28 2 1 Introduction Descriptive statistics involves the arrangement summary and presentation of data to enable meaningful interpretation and to support decision making Descriptive statistics methods make use of graphical techniques numerical descriptive measures The methods presented apply to both the entire population the population sample 29 2 2 Types of data and information A variable a characteristic of population or sample that is of interest for us Cereal choice Capital expenditure The waiting time for medical services Data the actual values of variables Interval data are numerical observations Nominal data are categorical observations Ordinal data are ordered categorical observations 30 Types of data examples Interval data Age income income Age 55 55 42 42 75000 75000 68000 68000 Weight Weight gain gain 10 10 5 5 Nominal Person Marital Marital status status Person 11 22 33 Computer Computer 11 22 33 married married single single single single Brand Brand IBM IBM Dell Dell IBM IBM 31 Types of data examples Interval data Nominal data With nominal data all we can do is calculate the proportion of data that falls into each category Age income income Age 55 55 42 42 75000 75000 68000 68000 Weight gain Weight gain 10 10 5 5 IBM IBM 25 25 50 50 Dell Compaq Compaq Other Other Dell 11 11 88 66 22 16 16 12 22 12 Total Total 50 50 32 Types of data analysis Knowing the type of data is necessary to properly select the technique to be used when analyzing data Type of analysis allowed for each type of data Interval data arithmetic calculations Nominal data counting the number of observation in each category Ordinal data computations based on an ordering process 33 Cross Sectional Time Series Data Cross sectional data is collected at a certain point in time Marketing survey observe preferences by gender age Test score in a statistics course Starting salaries of an MBA program graduates Time series data is collected over successive points in time Weekly closing price of gold Amount of crude oil imported monthly 34 2 3 Graphical Techniques for Interval Data Example 2 1 Providing information concerning the monthly bills of new subscribers in the first month after signing on with a telephone company Collect data Prepare a frequency distribution Draw a histogram 35 Example 2 1 Providing information Collect data Bills 42 19 38 45 29 23 89 35 118 04 110 46 0 00 72 88 83 05 There are 200 data points Prepare a frequency distribution How many classes to use Number of observations Less then 50 50 200 200 500 500 1 000 1 000 5 000 5 000 50 000 More than 50 000 Number of classes 5 7 7 9 9 10 10 11 11 13 13 17 17 20 Class width Range of classes 119 63 0 8 14 95 Largest Largest Largest Largest observation observation observation observation Smallest Smallest Smallest Smallest observation observation observation observation 15 36 Example 2 1 Providing information Draw a Histogram 37 Example 2 1 Providing information nnnnWhat information can we extract from this histogram 60 40 Bills 120 105 90 75 60 45 0 30 20 15 Frequency About half of all A few bills are in Relatively the bills are small the middle range large number 13 9 10 32 of large bills 80 71 37 108 18 28 14 60 38 Class width It is generally best to use equal class width but sometimes unequal class width are called for Unequal class width is used when the frequency associated with some classes is too low Then several classes are combined together to form a wider and more populated class It is possible to form an open ended class at the higher end or lower end of the histogram 39 Shapes of histograms There are four typical shape characteristics 40 Shapes of histograms Negatively skewed Positively skewed 41 Modal classes A modal class is the one with the largest number of observations A unimodal histogram The modal class 42 Descriptive Statistics Central Tendency mode median mean Dispersion standard deviation interquartile range IQR 43 Concepts 5 Normal Distribution Central tendency mean or average Dispersion standard deviation Non normal distributions 44 45 Concepts 6 What do we mean by central tendency Possibilities What is the most likely outcome
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