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Quantitative Methods
QMS 230
Douglas Mc Kessock

Chapter 1 Population: Consists of all of the members of a group about which you want to draw a conclusion - Parameter: Numerical measure that describes a characteristic of a population Sample: Portion of the population selected for analysis - Statistic: Numerical measure that describes a characteristic of a sample Discrete: When the data has a limit for example number of people on a bus, doesn’t go into decimals, and can’t be made more accurate Continuous: If it can go into decimals for example height, time, distance, area, volume, weight, money Categorical (Qualitative) Data Nominal – Its answers that have categories without order. Example:  Marital Status: Single, Married, Divorced or Widowed  Colors of cars: Red, Black, Blue, etc. Ordinal – Its answers that have categories with order but with rankings Example:  Letter Grades: A+, A, A-, B+, etc. st nd rd  Order in sports win: 1 , 2 , 3 , etc.  Professorial Rank: Lecturer, Assistant Professor, Professor, etc. Numerical (Quantitative) Data Summary Table: - A summary table indicates the frequency or percentage of Interval – It can’t be Doubled items in a set of categories so that you can see differences Example: between categories. - A summary table lists the categories in one column and the  Temperature frequency or percentage in a different column or columns.  Calendar Summary Table of Primary Banking Institution By Student Ratio – It can be Doubled Cumulative Example: Frequency Percent Valid Percent Percent Valid Bank of Montreal 3 11.5 11.5 11.5 CIBC 8 30.8 30.8 42.3  Hourly Income Citizen Bank 1 3.8 3.8 46.2 National Bank 1 3.8 3.8 50.0  Weight Royal Bank 7 26.9 26.9 76.9 Scotia Bank 2 7.7 7.7 84.6 TD Bank 4 15.4 15.4 100.0 Chapter 2 Total 26 100.0 100.0 Ordered Array – a sequence of data ranked from smallest to largest Frequency distribution: Bar Chart: - A summary table in which data - Shows Each Category are arranged into a numerically - to Compare %s in different Cats ordered class groupings - Comparing 2 cats together Pie Chart: - To observe the portion of the whole - Comparing 1 cat to another Stem and Leaf: - To organize a small amount of data in an easy to understand diagram Range: Max-Min Class Width: Range/7 Round to a nice Number Lowest Level Limit: Nice value near Min Frequency: # of Times it appears Relative Frequency: Histogram - Bar graph Presentation of a Frequency Polygon – Line graph Frequency/Total makes % Cumulative Frequency: Distribution Presentation of a Frequency - Frequency and normal point Distribution (%) Frequency Added Cumulative Relative - percentage histograms (rf) can - Frequency and Mid-points be used when comparing - percentage histograms (rf) can Frequency: % Added up be used when comparing Ogive  using a frequency distribution  needs crl  uses upper boundary for each class  When looking at calories per serving, when its less then do it normally, when its more than then usually subtract by a hundred  For %s when its most, do it normally, but when it says least then subtract % by hundred and then search Weighted Mean: X= data w= Grouped Data Mean: If its in Median: If mean and median weights (number of employees) frequency table, use midpoints as close, mean is the way to go XW+XW+XW…/total weight data If mean and median are not close, median is the way to go because
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