Statistics and Application to Business Decisions

Introduction

First, let define and distinguish the terms Population, and Sample


– If the data consist of all possible observations of a certain phenomenon, we call it Population
– If the data contains only a part of these observations, we call it Sample
Often, we need to represent a set of data in terms of a single (or a few) number
These are what we usually call Descriptive Statistics
Which kind of number we choose depends on the particular characteristics we
want to describe

  • We start considering those measures which describe the center or middle of a set of
    data, the measures of Central Location
    Vives

Median

Sometimes, samples contain very small or very large values that substantially affect
the Mean, and its ability in describing properly the data

  • These values are usually called outliers
    Example: Five light bulbs burned for 867,849,840,852,822 hours. The mean is 4230/5 = 846. If
    we record incorrectly the second value, that is 489 instead of 849, the mean would be 3870/5=774
    To avoid the problems related with the presence of outliers, we can use another
    measure of central location: the Median
  • The Median of a set of data is the value of the middle item when the data are
    ordered (in an increasing or decreasing order)
    Example: Eleven large corporations reported that in 2013 they made cash donations to
    9,16,11,19,11,10,13,12,6,9,12 colleges
    ! Arranging in an increasing order: 6 9 9 10 11 11 12 12 13 16 19
    ) The Median is 11
    Vives

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