STATISTICS An Introduction

Lecture #1 Topics Definition of Statistics Types of Statistics Why Communication Science Students Learn Statistics Population vs Sample Levels of Measurement

SOME DEFINITIONS OF STATISTICS The science of collecting, organizing, presenting, analyzing, and interpreting data to assist in making more effective decisions (Lind, .....) Facts shown in numbers (The Advanced Learner’s Dictionary of Current English, 1963)

TYPES OF STATISTICS Descriptive Statistics: methods of organizing, summarizing, and presenting data in an informative way Inferential Statistics/Inductive Statistics: the methods used to estimate a property of a population on the basis of a sample

DATA PRESENTATIONS Tables Bar Charts Pie Charts Line Charts Scatter Plot Diagram Histogram

TABLE

BAR CHART

PIE CHART

LINE CHART

SCATTER PLOT DIAGRAM

HISTOGRAM

Some Uses of Inferential Statistics Parameter estimation, e.g.: 1) What is the average total time in a day spent by American teenagers to watch youtube channels? 2) What percentage of US adults between the ages 18-29 are on Facebook? Hypothesis testing, e.g.: 1) Is there any correlation between people education level and their favoured news topics? 2) Was last week debate between two candidates in the 2019 Presidential Election effective in changing viewers’ preferences for the candidates?

Why must students majoring in Communication Science study statistics? Statistics roles as a quantitative method in researches on communication sciences, e.g.: “Do 3 C’s (Conflicts, Corruptions, Crimes) reportings on television and internet have influence on the sense of patriotism of Indonesian children?” In journalistic: Statistics teach us how to present data in a proper and informative way

INCORRECT vs CORRECT DATA PRESENTATION (1)

INCORRECT vs CORRECT DATA PRESENTATION (2)

POPULATION vs SAMPLE Population: (1) the entire set of individuals or objects of interest, (2) the entire set of measurements obtained from all individuals or objects of interest Sample: a portion, or part, of the population of interest

DATA CLASSIFICATION according to LEVELS OF MEASUREMENT Nominal Ordinal Interval Ratio

PROPERTIES OF NOMINAL LEVEL DATA The variable of interest is divided into categories or outcomes. There is no natural order to the outcomes.

PROPERTIES OF ORDINAL LEVEL DATA Data classifications are represented by sets of labels or names that have relative values. The data classified can be ranked or ordered.

PROPERTIES OF INTERVAL LEVEL DATA Data classifications are ordered according to the amount of the characteristic they possess. Equal differences in the characteristic are represented by equal differences in the measurements. Zero is relative

PROPERTIES OF RATIO LEVEL DATA Data classifications are ordered according to the amount of the characteristic they possess. Equal differences in the characteristic are represented by equal differences in the measurements. The zero point is the absence of the characteristic and the ratio between two numbers is meaningful (Zero is absolute)

HOW TO DETERMINE DATA LEVEL