Comm121 Study Notes
Summary Chapter 1-7
Chapter 1 * Population – consists of members of a group which you want to draw a conclusion * Sample – portion of population * Parameter – numerical measure that describes a characteristic of a population * Statistic – numerical measure that describes a characteristic of a sample * Descriptive statistics – collecting, summarizing and presenting data e.g. survey * Inferential statistics – drawing conclusions about a population based on sample data * Primary sources – you need to collect (start from scratch) * Secondary sources – other sources e.g. marketing/websites * Types of Data – Categorical, Numerical, Discrete, Continuous * Categorical Data – in words, yes or no, gender, colour * Numerical – numbers, how many times, income * Discrete – counting, whole numbers * Continuous – measuring, height, weight. Can have partial numbers e.g. 4.73 * Levels of Measurement and Measurement Scales – Ratio Data, Interval Data, Ordinal Data, Nominal Data * Ratio Data – true zero exists, only positive values e.g. Height, weight, age (numerical) * Interval – no true zero, negative and positive values e.g. temp and dates (numerical data) * Ordinal – ordered categories e.g. rankings, student letter grades (categorical) * Nominal – categories, no ordering or direction e.g. martial status, type of car, gender (categorical) * Summary * Population vs. sample * Parameter vs. statistics * Data collection sources * Categorical vs. numerical data * Discrete vs. continuous data * Nominal vs. ordinal data * Interval and ratio scales
Chapter 2 * Table and Charts for Categorical Data – Graphing (Bar charts and pie charts), Summary table * Bar and Pie Charts – used for qualitative data * Tables and Charts for Numerical Data – Ordered Array (Stem-and-leaf plot), Frequency Distributions Cumulative Distributions (Histogram, Polygon, Ogive) * Ordered Array
Chapter 1 * Population – consists of members of a group which you want to draw a conclusion * Sample – portion of population * Parameter – numerical measure that describes a characteristic of a population * Statistic – numerical measure that describes a characteristic of a sample * Descriptive statistics – collecting, summarizing and presenting data e.g. survey * Inferential statistics – drawing conclusions about a population based on sample data * Primary sources – you need to collect (start from scratch) * Secondary sources – other sources e.g. marketing/websites * Types of Data – Categorical, Numerical, Discrete, Continuous * Categorical Data – in words, yes or no, gender, colour * Numerical – numbers, how many times, income * Discrete – counting, whole numbers * Continuous – measuring, height, weight. Can have partial numbers e.g. 4.73 * Levels of Measurement and Measurement Scales – Ratio Data, Interval Data, Ordinal Data, Nominal Data * Ratio Data – true zero exists, only positive values e.g. Height, weight, age (numerical) * Interval – no true zero, negative and positive values e.g. temp and dates (numerical data) * Ordinal – ordered categories e.g. rankings, student letter grades (categorical) * Nominal – categories, no ordering or direction e.g. martial status, type of car, gender (categorical) * Summary * Population vs. sample * Parameter vs. statistics * Data collection sources * Categorical vs. numerical data * Discrete vs. continuous data * Nominal vs. ordinal data * Interval and ratio scales
Chapter 2 * Table and Charts for Categorical Data – Graphing (Bar charts and pie charts), Summary table * Bar and Pie Charts – used for qualitative data * Tables and Charts for Numerical Data – Ordered Array (Stem-and-leaf plot), Frequency Distributions Cumulative Distributions (Histogram, Polygon, Ogive) * Ordered Array