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CONCORDIA UNIVERSITY / Communications / COMM 215 / What is multistage cluster?

What is multistage cluster?

What is multistage cluster?


School: Concordia University
Department: Communications
Course: Business Statistics
Professor: Wissam nawfal
Term: Spring 2017
Cost: 50
Name: Study guide for Midterm 1
Description: covers Chapter 1,2,3,4,5,6 for midterm for Chapter 5,6 look for examples in the textbook, I marked the page in the notes
Uploaded: 10/19/2017
13 Pages 64 Views 1 Unlocks

Business Analytics

  • Descriptive, represent easy to understand visual summaries
  • Predictive : find anomalies, patterns to predict future outcome
  • Data mining : extract from large amounts of data
  • Prescriptive analytics : looks at variables and constraints
  • Predictive Analytics Applications

    1. Anomaly detection
    2. Association learning : find items that tend to co - occur and find rules
    3. Classification : assign in categories / classes
    4. Cluster detection : find natural grouping, without assigning categories
    5. Prediction :
    6. Factor detection : large number of correlated variables, find uncorrelated variables

    ratio : quantitative relation between 2 amounts →

    interral : use when ratio is not meaningful → temperature

    ordinal : use when there is meaningful ordering → teaching effectiveness We also discuss several other topics like What does carmagnole (kar-man-yole’) refer to?

    nominative : no meaningful of ordering → gender

    stratified random : divide population into non overlapping groups (strata), select random sample from strata

    multistage cluster : divide population into sub - population (clusters) select clusters to sample

    systematic sampling : list population, select random start point, sample each nth element

    If you want to learn more check out Define systematics in biology.

    Types of survey questions

    Types of surveys

    dichotomous : yes / no answers

  • phone
  • multiple choices :

  • mail
  • open - ended questions

  • web
  • personal interview
  • Chapter 1

    variable : any characteristic of an element

    quantitative : numbers that represent quantities

    qualitative : falls into categories e.g. eyes color

    Cross - sectional data : data collected at the same or approximately the same point in time

    Time series data : data collected over different time periods  

    Types of data sources

  • existing sources : data already gathered by public / private sources
  • experimental studies :         
  • observational studies :         we collect ourselves for specific purpose
  • Don't forget about the age old question of Define psychological disorder.

    data warehousing : process of centralized data management

    big data : massive amounts of data

    population : all elements from a set of data

    sample : subset of population

    census : examination of all the population measurements

    descriptive statistics :  science of describing the important aspects of a set of measurements

    statistical inference : science of using a sample of measurements to make generalizations If you want to learn more check out What is the lewis structure for carbon?

    statistical model : set of assumptions about how samples are selected

    probability sampling : sampling where we know the chance that each element in the population will be included in the sample

    convenience sampling : convenient to sample

    voluntary response sampling : participants self - select  

    judgement sampling : person extremely knowledgeable about population selects population that he / she feels are the most representable

    target population : entire population of interest

    sample frame : list from which we select sample

    sampling error : difference between numerical descriptor and corresponding descriptor of sample

    undercoverage : when some individuals are excluded when selecting sample

    nonresponse : when some individuals were supposed to be included are not included

    bias : when opinions of some who did survey vary a lot from these did not participate in survey

    errors of observation : when recorder misobserves and marks wrong

    recording error : when recorder incorrectly marks an answer

    response bias : when respondents do not tell the truth

    Class 2

    September 18, 2017

    Chapter 2 Descriptive Statistics

  • Qualitative data
  • frequency distribution → values and their frequency
  • If you want to learn more check out What are the benefits of globalized markets?

    relative frequency → a proportion = frequency / total # of observations

    percent frequency → relative frequency ✕ 100 %

    We also discuss several other topics like What is the main evidence upon which the modern theory of evolution is based?

  • bar charts → vertical rectangles in a graph to represent frequency
  • pie charts → circle with different segments to represent frequency for relative or percent frequency distribution
  • pareto charts → bar height represent frequency
  • bars arranged in decreasing height from left to right

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