Applied Business Research

Quantitative analysis.

Types of variables and level of measurement. 1.2.

Definition Quantitative variable - information is reported numerically.

Definition Discrete variables can only assume certain values and there are usually “gaps” between values..

Summary of Types of Variables. Types of variables Qualitative Quantitative Brand of PC Marital status Hair color Discrete Continuous Children in a family Strokes on a golf hole Tv sets owned Amount of income tax paid Weight of a student Yearly rainfall in Tampa ,FLz.

Nominal level - data that is classified into categories and cannot be arranged in any particular order e.g : eye color, gender, religious affiliation.

Cuddle companions Great entertainers Bathe themselves Independent 0.4 0.37 0.13999999999999999 0.09.

Résultat de recherche d'images pour "richter scale images HD".

Image associée. Interval-Level Data. Properties: 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..

Résultat de recherche d'images pour "kitten". Résultat de recherche d'images pour "fat cat".

Why is the Level of Measurement Important?. The level of measurement dictates the calculations that can be done to summarize and present the data. It is used to determine the statistical tests that should be performed on the data..

Level of measurement Nominal Ordinal Data may only be classified Interval Ratio Data are ranked Rank in class Team standings in the U23 Car brand Jersey number of football players Meaningful difference between values Temperature Dress size Meaningful 0 point and ratio between values Number of patients seen Number of sales made.

Exercise. 13. Complete the following exercises from your textbook (access Kortext) 13 from page 15 19 from page 17 Submit on Canvas as a one file upload, on the following link: https://buv.instructure.com/courses/1781/assignments/10574.

Software that can be used. JASP https://jasp-stats.org/download/ Excel SPSS R statistical analysis https://cran.r-project.org/bin/windows/base/.

Ethics and Statistics. Practice of statistics should be based on integrity and honesty when: Collecting data Analyzing data Reporting results and conclusions based on the data.

Descriptive Statistics. Used when we are only interested in the specific group from which the measurements are taken. The facts and figures, whether graphical or numerical, are usually referred to as 'the statistics' in the media. Much business data will be descriptive in nature. In the next five weeks you will learn how to display data graphically and summarise it numerically..

Inferential Statistics. Used to infer something about the population when we only have the data from a sample. The sample is analysed to produce the sample summary statistics from which we can infer values for the parent population. The summary statistics from the sample are usually referred to as the sample statistics and the corresponding measure estimated for the population as a population parameters ..

Describing data. Chapter 2. 18.

Presentation of the dataset. Throughout the course, we will use the Applewood dataset you can find in your Gdrive folder Applewood is a Canadian car dealer. We will use the dataset for the second hand cars sold.

Vehicle-Type Frequency Sedan 72 SUV 54 Hybrid 9 Compact 27 Truck 18.

Bar Charts. 21. Definition: BAR CHART A graph that shows qualitative classes on the horizontal axis and the class frequencies on the vertical axis. The class frequencies are proportional to the heights of the bars..

22. Pie Charts. Definition: PIE CHART A chart that shows the proportion or percent that each class represents of the total number of frequencies..

Bar Chart and Pie Chart Example. SkiLodges.com is test marketing its new website and is interested in how easy its website design is to navigate. It randomly selected 200 regular Internet users and asked them to perform a search task on the website. Each person was asked to rate the relative ease of navigation as poor, good, excellent, or awesome. The results are shown in the table..

Bar Chart and Pie Chart Example. 24. Ease of navigation Frequencies Relative frequency Poor 10 5% Good 30 15% Excellent 58 29% Awesome 102 51% 160 100%.

Example: Frequency distribution for profits. Category Intervals Profit Lower bound Upper bound 1 [ 200 ; 600 [ 8 2 [ 600 ; 1000 [ 11 3 [ 1000 ; 1400 [ 23 4 [ 1400 ; 1800 [ 38 5 [ 1800 ; 2200 [ 45 6 [ 2200 ; 2600 [ 32 7 [ 2600 ; 3000 [ 19 8 [ 3000 ; 3400 [ 4.

Frequency Distribution. Class interval : The class interval is obtained by subtracting the lower limit of a class from the lower limit of the next class. Class frequency : The number of observations in each class. Class midpoint : A point that divides a class into two equal parts. This is the average of the upper and lower class limits..

Relative Class Frequencies. Class frequencies can be converted to relative class frequencies to show the fraction of the total number of observations in each class. A relative frequency captures the relationship between a class total and the total number of observations..

Displays of Frequency Distributions. Two commonly used graphic forms are: Histograms Cumulative frequency distributions.

Histogram. 29. Definition: HISTOGRAM A graph in which the classes are marked on the horizontal axis and the class frequencies on the vertical axis. The class frequencies are represented by the heights of the bars and the bars are drawn adjacent to each other..

Cumulative Frequency Distribution. 30. Categories Cumulative frequency Found by Less than 600 8 8 Less than 1000 19 8 + 11 Less than 1400 42 8 + 11 + 23 Less than 1800 80 8 + 11 + 23 + 38 Less than 2200 125 8 + 11 + 23 + 38 + 45 Less than 2600 157 8 + 11 + 23 + 38 + 45 + 32 Less than 3000 176 8 + 11 + 23 + 38 + 45 + 32 + 19 Less than 3400 180 8 + 11 + 23 + 38 + 45 + 32 + 19 + 4.

Cumulative Frequency Distribution. 31. 600 1000 1400 1800 2200 2600 3000 3400 4.4444444444444446E-2 0.10555555555555556 0.23333333333333334 0.44444444444444442 0.69444444444444442 0.87222222222222223 0.97777777777777775 1.