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ECN 211 Statistics for Economics I

ECN 211 Statistics for Economics I. LECTURE 1. What are statistics?. A way to get information from data. A broad range of techniques, procedures for gathering, organizing, analyzing and displaying quantitative data. Key concepts.

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ECN 211 Statistics for Economics I

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  1. ECN 211Statistics for Economics I LECTURE 1 Assist. Prof. Evrim Turgutlu

  2. What are statistics? • A way to get information from data. • A broad range of techniques, procedures for gathering, organizing, analyzing and displaying quantitative data. Assist. Prof. Evrim Turgutlu

  3. Key concepts Population: It represents all the elements of some specified type. E.g. All the households in a country: a population of households All the economics students in Turkey: a population of economics students Gathering data on every item in a population such as all the households in a country is in many situations too costly or too time consuming. In such cases,information is obtained from part of a population. Sample: A set of elements consisting a part of a population is called a sample of the population. • Variable: It is any characteristic of a population or sample that is of interest to us. Assist. Prof. Evrim Turgutlu

  4. Population vs. sample E.g. A sample of households in a country A sample of economics students in Turkey Assist. Prof. Evrim Turgutlu

  5. Key concepts • Parameter: A descriptive measure of a population. • Statistic: A descriptive measure of a sample. Assist. Prof. Evrim Turgutlu

  6. Kinds of statistics • There are two main kinds of statistics: • Descriptive statistics: These are used to describe a set of quantitative data. It deals with organizing, summarizing and presenting data in a convenient and informative way. There are graphical and numerical techniques in descriptive statistics. 2.Inferential statistics: It is the process of making an estimate, prediction or decision about a population based on sample data. In order to achieve this goal a sample should be selected in a manner such that each element of the population has an equal chance of being included in the sample. Also selection of one member should have no effect on the selection of any other member. Assist. Prof. Evrim Turgutlu

  7. Key concepts Variable: It is any characteristic of a population or sample that is of interest to us. E.g. What are the main characteristics of an economy? GDP, Inflation, unemployment, interest rate... Data: They are actual measures of variables. Assist. Prof. Evrim Turgutlu

  8. Types of data • Quantitative data: Values are real numbers and arithmetic calculations are valid. E.g. Age, income, weight... • Qualitative data: Values are names of possible catgories. E.g. Gender, race, occupation... • Ranked data: Values represent the ranked order of responses. E.g. Quality of a product 1. Excellent, 2. Good, 3. Fair, 4. Poor !!! Knowing the type of data being used is important because it is one of the factors that determines the statistical techniques should be used.!!! Assist. Prof. Evrim Turgutlu

  9. Types of data Data can be classified according to whether observations are measured at the same time (cross-sectional data) or whether they represnt measurements at successive points in time (time-series data). Assist. Prof. Evrim Turgutlu

  10. DESCRIPTIVE STATISTICS When you have a huge mass of data, reducing them yo an easily comprehended summary is a very important thing. First, we will learn about those techniques. Assist. Prof. Evrim Turgutlu

  11. FREQUENCY DISTRIBUTION Frequency distributions organize and summarize data by displaying in a table how often specific scores were obtained. Step 1. Constructing frequency distribution table Step 2. Constructing charts and graphs that give visual representation of patterns which exist in data sets. Assist. Prof. Evrim Turgutlu

  12. FREQUENCY DISTRIBUTION Frequency distribution is a tabular summary of a set of data showing the frequency (or number) of items in each of several nonoverlapping classes. Assist. Prof. Evrim Turgutlu

  13. FREQUENCY DISTRIBUTION Example: Consider the quantitative data. The data provide the weekly earnings of 20 manufacturing workers in dollars. What information can you get from these dta? Assist. Prof. Evrim Turgutlu

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