Chapter 1.1 - Stats - Statistics Data and Statistical
chapter 1: STATS – STATISTICS DATA AND STATISTICAL THINKING
1.1 The science of statistics * Statistics - is the science of data. It involves collecting, classifying, summarising, organising, analysing, and interpreting numerical information.
1.2 types of statistical applications in business * Descriptive Statistics - describe collected data. Utilizes numerical and graphical methods to look for patterns in data, summarize the information in the data and to present the information in a convenient form * Inferential Statistics – utilizing sample data to make estimates, predictions or other generalizations about a larger data set. * Estimation (Making conclusions of a population based on sample) * Hypothesis Testing (Testing on a belief) * Confidence Interval (33 +/8) %
1.3 fundamental elements of statistics * Experimental Unit – object (eg: person, thing, transaction, or event) of interest for which data is collected * Example – graduating NBS students in 2013 * Example – FOX viewers * Example – Cola consumers * Population – the set of units we are interested in learning about * Example – all 1200 graduating students at NBS in 2013 * Example – all FOX viewers * Example – all Cola consumers * Variable – characteristic or property of a single experimental unit * Any particular characteristic may vary among the experimental units in a population * Example – salary at first job after graduation * Example – Age (in years) of each viewer * Example – Cola preference * Sample – subset of population * Example – 100 graduating students who replied to online survey * Example – 200 FOX viewers selected by the executive * Example – 1,000 cola consumers selected from the population * Statistical Inference – generalization about a population based on sample data * Example – the average salary on
1.1 The science of statistics * Statistics - is the science of data. It involves collecting, classifying, summarising, organising, analysing, and interpreting numerical information.
1.2 types of statistical applications in business * Descriptive Statistics - describe collected data. Utilizes numerical and graphical methods to look for patterns in data, summarize the information in the data and to present the information in a convenient form * Inferential Statistics – utilizing sample data to make estimates, predictions or other generalizations about a larger data set. * Estimation (Making conclusions of a population based on sample) * Hypothesis Testing (Testing on a belief) * Confidence Interval (33 +/8) %
1.3 fundamental elements of statistics * Experimental Unit – object (eg: person, thing, transaction, or event) of interest for which data is collected * Example – graduating NBS students in 2013 * Example – FOX viewers * Example – Cola consumers * Population – the set of units we are interested in learning about * Example – all 1200 graduating students at NBS in 2013 * Example – all FOX viewers * Example – all Cola consumers * Variable – characteristic or property of a single experimental unit * Any particular characteristic may vary among the experimental units in a population * Example – salary at first job after graduation * Example – Age (in years) of each viewer * Example – Cola preference * Sample – subset of population * Example – 100 graduating students who replied to online survey * Example – 200 FOX viewers selected by the executive * Example – 1,000 cola consumers selected from the population * Statistical Inference – generalization about a population based on sample data * Example – the average salary on