Lesson 2 Basic Statistical Concepts PDF

a. Statistics b. Elements c. Variables d. Types of Data e. Scale of Measurement f. Population and Sample Introduction Statistics Branch of mathematics that deals with the systematic method of collecting, classifying, presenting, analyzing and interpreting all kinds of data pertinent to...

a. Statistics b. Elements c. Variables d. Types of Data e. Scale of Measurement f. Population and Sample Introduction Statistics Branch of mathematics that deals with the systematic method of collecting, classifying, presenting, analyzing and interpreting all kinds of data pertinent to the study being considered so that meaningful conclusion can be drawn. Statistics The Five Essential Processes in Statistics 1. COLLECTION 2. CLASSIFICATION 3. PRESENTATION 4. ANALYSIS 5.INTERPRETATION Descriptive Statistics gathering, classifying and presenting data and the collection of summarizing values to describe group characteristics of data. includes collection, presentation and description of numerical data. Descriptive Statistics are brief informational coefficients that summarize a given date set, which can be either a representation of the entire population or a sample. are broken down into measures of central tendency which includes mean, median and mode and measures of variability (spread) which include standard deviation, variance, minimum and maximum variables, kurtosis and skewness. Inferential Statistics pertains to the methods of dealing with making inferences, estimates or predictions about a large set of data using the information gathered. refers to techniques of interpreting the values resulting from descriptive techniques and using them in drawing conclusions about population on a representative sample Inferential Statistics it allows researcher to make assumptions about a wider group, using a smaller portion of group as guideline are used to generalize about large groups such as estimating average demand for a product surveying a sample of consumers’ buying habit or to attempt to predict future events, such as projecting the future of a security or asset class based on returns in a sample period. Elements The five words population, sample, parameter, statistic (singular), and variable form the basic vocabulary of statistics. Elements Population - All the members of a group about which you want to draw a conclusion Sample - The part of the population selected for analysis Parameter - A numerical measure that describes a characteristic of a population. Statistic - A numerical measure that describes a characteristic of a sample Variable - A characteristic of an item or an individual that will be analyzed Variables It is a characteristic or attribute of a person or object, which assumes different values (numerical) or labels (quantitative) Categorical Variable A variable that is made up of different types or categories of a phenomenon The values of these variables are selected from an established list involving a counted or measured of categories. Categorical Variable Categorical Nominal Variable ▪Describes a name, label or category without natural order Examples: Sex (Male or Female) Name Blood Type Hair Color Categorical Variable Categorical Ordinal Variable ▪Values are defined by an order relation between the different categories Examples: Socio Economic Status Ratings Educational Level Satisfaction Quantitative Variable A variable that varies in degree or amount of phenomenon is a quantifiable characteristic whose values are numbers  Quantitative Variable Quantitative Continuous Variable ▪assume an infinite number of real values within a given interval Quantitative Discrete Variable ▪assume only a finite number of real values within a given interval. Independent Variable A variable that is presumed to cause changes in another variable; causal variable Variable you manipulate in order to affect outcome of an experiment Dependent Variable A variable that changes because of another variable; the effect or outcome variable Variable that represents the outcome of the experiment Mediating Variable A variable that comes in between other variables; helps to explain the process through which variables affect one another Explains the process through which two variables are related Mediator variables specify how or why a particular effect or relationship occurs. Moderator Variable type of variable that affects the relationship between a dependent variable and an independent variable. may increase or decrease the strength of a relationship, or change the direction of a relationship. Moderators indicate when or under what conditions a particular effect can be expected. DATA set of values collected for the response variable from each of the elements belonging to the sample. Quantitative Data Refers to quantities, counts, or measurements Numerical in nature Quantitative Data Quantitative Discrete Data ▪Values can be counted using integral values Quantitative Continuous Data ▪Expressed in approximation or measurements Qualitative Data Refers to data that can be observed but not measured. Represent differences in quality, character or kind but not in amount. Other Types Primary Data Binary: Secondary Data Ordered Categories Internal Data Unordered Categories External Data Count SCALE of MEASUREMENT Relates to the rules used to assign scores and is an indicator of the kind of information that the scores provide. MEASUREMENT – the process of assigning a numerical value to a variable TYPES of Measurement Scales Nominal Ordinal Interval Ratio  Nominal Scale ❖Measures of identity ❖Use numbers for the purpose of identifying names or membership in a group or category. ❖is an unordered set of categories identified only by name. ❖Nominal measurements only permit you to determine whether two individuals are the same or different. Example: Gender (male and female)  Ordinal Scale ❖Data are ranked from “bottom to top” or “low to high” manner ❖The data can be arranged in an ordering scheme or ranked ❖Measurement used on ranking individuals or objects ❖Ordinal measurements tell you the direction of difference between two individuals. Example: student evaluation  Interval Scale ❖Are numbers that reflect differences among items ❖Possesses the properties of the nominal and ordinal levels ❖Measurement used on ranking individuals or objects Example: scores in a test  Ratio Scale ❖Data can be classified and be placed in a proper order ❖Possesses all the properties of the nominal, ordinal and interval levels Example: weight  Properties of Measurement Scales Scale of Classify Oder Equal Limits Absolute Zero Measurement NOMINAL Yes No No No ORDINAL Yes Yes No No INTERVAL Yes Yes Yes No RATIO Yes Yes Yes Yes POPULAT ION & SAMPLE  Population ❑ The totality of subjects (people, animals or objects) under consideration. ❑ Refers to the entire group that is under study or investigation. ❑ Refers to groups or aggregates of people, objects, materials, events, or things of any form.  Sample ❑ The portion chosen from a population. ❑ It is a subset taken from a population, either by random or nonrandom sampling technique. ❑ Subgroup of the population. MIND SETTING