Summary Managerial Statistics

ISBN-10 1111534632 ISBN-13 9781111534639
343 Flashcards & Notes
6 Students
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This is the summary of the book "Managerial Statistics". The author(s) of the book is/are Gerald Keller. The ISBN of the book is 9781111534639 or 1111534632. This summary is written by students who study efficient with the Study Tool of Study Smart With Chris.

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Summary - Managerial Statistics

  • 1 What Is Statistics

  • Range
    Largest number - Smallest number
  • 1.1 Key Statistical Concepts

  • Population
    The group of all items of interest to a statistics practitioner.
  • How do you call the group of all items that are of interest to a statistics practitioner?
  • Parameter
    A descriptive measure of a population.
  • How do you call a descriptive measure of a population?
  • Sample
    A set of data drawn from the studied population.
  • How do you call a set of data drawn from the studied population?
  • Statistic
    A descriptive measure of a sample.
  • How do you call a descriptive measure of a sample?
  • Statistical inference
    The process of making an estimate, prediction, or decision about a population based on sample data.
  • How do you call the process of making an estimate, prediction, or decision about a population based on sample data?
    Statistical inference
  • Confidence level
    The proportion of times that an estimating procedure will be correct.
  • How do you call the proportion of times that an estimating procedure will be correct?
    Confidence level
  • Significance level
    How frequently the conclusion will be wrong.
  • How do you call the measure of how frequently a conclusion will be wrong?
    Significance level
  • 2 Graphical Descriptive Techniques I

  • What is a variable?
    A characteristic of a population or sample
  • What is a value?
    The possible observations of a variable
  • What are data?
    The observed values of a variable
  • What are the 4 types of measurement levels?
    1. Interval (quantitative)
    2. Nominal (qualitative)
    3. Ordinal (qualitative)
    4. Ratio (quantitative)
  • What is the interval data of measurement?
    Real numbers, such as heights, weights, incomes, etc. Also known as quantitative or numerical data. There is an arbitrary zero point, that we as humans chose. E.g temperature. All calculations are valid, and data may be treated as ordinal or nominal.
  • What is the nominal level of measurement?
    Values are the arbitrary numbers that represent categories. E.g. man or woman Only calculations based on the frequencies or percentages of occurrence are valid. Data may not be treated as ordinal or interval.
  • What is the ordinal level of measurement?
    Values must represent the ranked order of the data. Calculations based on an ordering process are valid. Data may be treated as nominal but not as interval.
  • What is a frequency distribution?
    A categorisation of nominal values, and the counts of the categories.
  • What is a relative frequency distribution?
    Lists the values into categories and the proportion with which each occurs.
  • What are the 2 graphical techniques we use to describe nominal data?
    1. Pie chart - relative frequency
    2. Bar chart - normal/absolute frequency
  • What is the ratio level of measurement?
    The point of zero is meaningful, meaning that at 0 you really have nothing. E.g. Age, length, etc.
  • What are the 2 types of graphical techniques used to describe ordinal data?
    Also bar chart and pie chart, but the only difference is that the values at the horizontal axis of the bar chart have a logical order, as do the values in the pie chart. The pie chart is also arranged clockwise
  • What graphical techniques are used to describe interval and ratio data?
    - Histograms
    - Stem leaf display
    - Ogive
  • What is a histogram?
    Gives a clear summary of the set of data. Is drawn with a frequency table that counts the occurrences of a certain interval
  • What is the formula of Sturges?
    The formula that can help you decide how many intervals/classes you should have based on the number of observations. 1 + 3.3log(n), with n = the number of observations. The formula only works with more than 30 observations
  • What is the class width formula?
    (largest observation - smallest observation)/ number of classes
  • What are the 6 shapes a histogram can take on?
    1. Symmetrical - a vertical line down the middle would lead to both sides being identical in shape and size
    2. Positively skewed - A peak at the beginning with a long tail extending to the right
    3. Negatively skewed - Peak later in the histogram with tail extending to the left
    4. Unimodal - 1 peak
    5. Bimodal - 2 peaks
    6. Bell shaped - specific histogram for normal distribution
  • What is a stem-leaf display?
    The stem is the first digit of the class, the leaf are all the second digits that fall within the class. E.g. 1 stem, 00122233 leaf
  • What is cumulative frequency?
    The frequency of the class added to the frequency of the previous class.
  • What is an ogive?
    A cumulative frequency polygon, shows the cumulative frequencies. The upper limit of the class is always displayed on the x axis, on the y axis the percentages. The highest percentage is always 100%
  • What are the two types of time measurements?
    1. Cross-sectional data - measures multiple observations at the same time
    2. Time-series data - measures the same observations at different moments in time
  • What is a line chart?
    The chart that is used to depict time-series data. The x-axis displays the time.
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