Introduction to Statistical Data Analysis - Part 1

Data Management SIX BASIC STEPS Business Research Methods 1 | Business Research Methods 2 |  Nominal Data Qualitative The values cannot be (categorical/Attributes) ranke...

Data Management SIX BASIC STEPS Business Research Methods 1 | Business Research Methods 2 |  Nominal Data Qualitative The values cannot be (categorical/Attributes) ranked  Data that refers to Gender, race, Use classification name citizenship, colour, etc. code Ordinal Data numbe according to some rs characteristic or The values can be (1, 2, attribute ranked and likert scale is …)  Data is classified using used code numbers Feeling (dislike-like), colour (dark-bright), Type Discrete Data etc. of The values can be counted and Data finite Quantitative Number of student, number of (Numerical) cat, number of defect, etc. Continuous Data  Data can be counted or The values can be placed within measured two specified values, obtained by  Data can be ordered or measuring, have boundaries, ranked and shall be rounded to require decimal places Ratio/Interval Data Weight, age, salary, temperature, etc. Business Research Methods 3 | Level of Measurement The way a set of data is measured is called its level of measurement. Correct statistical procedures depend on a researcher being familiar with levels of measurement. Four levels of scale measurement include 1. the nominal scale, 2. the ordinal scale, 3. the interval scale, and 4. the ratio scale. Business Research Methods 4 | The Nominal Scale The properties of nominal data are as follows: 1.Data categories are mutually exclusive (an object can belong to only one category/no overlapping in category). 2.Data categories have no logical order. Examples are sex, color of hair/eyes, ethnic background, makes of car and so on. Summary: a nominal scale simply classifies without order. Assigns a value to an object for identification or classification purposes (e.g. : 1 = Male, 2 = Female). Most elementary level of measurement. Business Research Methods 5 | The Interval Scale The properties of interval data are as follows: 1. Data categories are mutually exclusive. 2. Data categories have some logical order. 3. Data categories are scaled according to the amount of the particular characteristic they possess. 4. Equal differences in the characteristic are represented by equal differences in the numbers assigned to the categories. 5. The point zero is just another point on the scale. An Example of interval scale is temperature (0o Celsius, 32o F). Summary: Capture information about differences in quantities of a concept. Have both nominal and ordinal properties. Business Research Methods 6 | The Ratio Scale The properties of ratio data are as follows: 1. Data categories are mutually exclusive. 2. Data categories have some logical order. 3. Data categories are scaled according to the amount of the particular characteristic they possess. 4. Equal differences in the characteristic are represented by equal differences in the numbers assigned to the categories. 5. The point zero reflects an absence of the characteristic. Examples of ratio scales are income, age, weight, height, score (including composite/mean composite score), etc. Summary: Highest form of measurement. Have all the properties of interval scales with the additional attribute of representing absolute quantities. Absolute zero. Business Research Methods 7 | The Ordinal Scale The properties of ordinal data are as follows: 1. Data categories are mutually exclusive. 2. Data categories have some logical order. 3. Data categories are scaled according to the amount (e.g. : Grade A = 80-90, A+ = 91-100) of the particular characteristic they possess. Examples are course grade: A+, A, B+, B, B-, C+, C, C-, D, D- and F; level of satisfaction: low, medium and high and so forth. Summary: Ranking scales allowing things to be arranged based on how much of some concept they possible. Have nominal properties Business Research Methods 8 | EXAMPLE 1 Determine the correct data type (quantitative or qualitative). Indicate whether quantitative data are continuous or discrete. Hint: Data that are discrete often start with the words “the number of.” a) The number of pairs of shoes you own h) Movie ratings b) The type of car you drive i) Political party preferences c) The place where you go on vacation j) Weights of sumo wrestlers d) The distance it is from your home to the k) Amount of money (in dollars) won playing nearest grocery store poker e) The number of classes you take per school l) Number of correct answers on a quiz year. m) Peoples’ attitudes toward the government f) The tuition for your classes n) IQ scores g) The type of calculator you use Answer Items a, e, f, k, and l are quantitative discrete; items d, j, and n are quantitative continuous; items b, c, g, h, i, and m are qualitative.