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Get Full Access to University of Louisiana at Lafayette - QMET 352 - Class Notes - Week 3
Get Full Access to University of Louisiana at Lafayette - QMET 352 - Class Notes - Week 3

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UNIVERSITY OF LOUISIANA AT LAFAYETTE / College of Business / BUS 352 / Is social security number nominal or ordinal?

# Is social security number nominal or ordinal? Description

##### Description: Important: The entire objective part on the next exam consist of these notes! If you missed class after Mardi Gras, you will need these notes. The next exam will not be open book.
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Feb. 11th 2016Key Box: ***: Know for test

## Is social security number nominal or ordinal?

EXAM 2 (NOT OPEN BOOK) will consist of:

∙ 9 Multiple Choice

∙ 3 Fill-in-the-blank

∙ 1 True/ False

∙ 3 problems to work

The entire objective part on the exam  consist of these notes!

On exam, know: names, ranks, definitions, and examples!

***: Definition ***: Titles

ALL DEFINITIONS IN THESE NOTES WILL BE ON THE NEXT EXAM!

❖ 4 Types of Data

o Types of measurement scales= Data (same thing)

## What type of data measurement has a true zero point?

o Ranked from weakest to strongest

▪ Below is the correct order!

1. Nominal (weakest): Numbers are used to represent names (names/classification, etc.) a. Ex: Social Security (most used version of this type of data) Don't forget about the age old question of What are the six economic indicators?

b. Weak ???? Calculate mean- doesn’t really tell you anything

2. Original: Data which has been ranked OR put into order If you want to learn more check out What is the study of human movements by identifying the anatomical elements?
If you want to learn more check out If 200.0 g of zinc sulfide contains 134.2 g of zinc, how many grams of sulfur can be obtained from 1.18 kg of zinc sulfide?
Don't forget about the age old question of What group does benzopyrene belong to?

a. Can’t do much with it, but you do use it to put things in rank

b. Ex: Sport rankings, movie rankings, etc.

3. Interval: Data where the numbers mean something, but there is NO ONE TRUE ZERO  POINT

a. You can find the mean, but no true zero point

## What is the most appropriate accuracy measure in situations where you need to compare forecasting methods for different time periods?

b. Ex: Temperature ???? each version (Fahrenheit or Celsius) has their own different  zero point

4. Ratio (strongest): Data where the numbers mean something and there is a true zero a. Ex: GPA—The numbers tell you something

b. MOST OF WHAT WE DO IS RATIO DATA!

❖ Time Series

∙ A set of values/data measured at successive points in time over a given time period ∙ Reference example problems given in class

o 1st column= Time

o 2nd column= Data We also discuss several other topics like What is the purpose of capitalism?

∙ We will use it to measure future data

o What we will be doing: Taking what is given and forecasting future data A. Components of a time series:

1. Trend – the gradual shifting of the time series value usually because of long term  factors.

a. Long-term = more than a year

b. Long- term factors that affect trends include:

i. Changes in the population ???? change in size If you want to learn more check out What is a valence electron?

ii. Changes in the demographic characteristics of population

iii. Changes in technology

iv. Changes in consumer preferences

v. Economic changes???? mainly inflation

2. Cyclical – an up and down movement over a long time period ???? usually last MORE

THAN a year

a. Like a legit cycle of events:

3. Seasonal – shows changes in the historical data within ONE YEAR usually because of  seasonal influences

a. Seasonal change ???? weather

4. Irregular – explains changes in actual time series values which cannot be explained  by any other components.

a. Irregular components CANNOT be predicted using historical data. Usually  due to acts of God: unanticipated, nonrecurring factors.

i. Ex: tornado, hurricane, flood, etc.

1. One can see it coming, cannot predict what it will do or when

another will come

B. Time Series Forecasting using SMOOTHING method:

a. Smoothing – smoothing out irregular factors because smoothed values have less  variation than the raw data

b. Smoothing techniques:

i. Simple moving average (simplest)

ii. Weighted moving average

1. Problem will give “weight” ???? check problem #2 for example

iii. Exponential smoothing (hardest to grasp)

∙ If the problem sates just “moving average”, go with the simple moving  method ???? check prob. #1 for example

∙ After working all, we can determine which way to work it is best

NOTE FROM DR.TANNER:

PLEASE ONLY USE THESE NOTES AS A REFERENCE.  DO NOT MISS CLASS JUST BECAUSE YOU CAN BUY THE NOTES.

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