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Probability 2 - Coggle Diagram

- - - - Quantitative data may be either discrete or continuous.
        
        All data that are the result of counting are called quantitative discrete data.
        
        Data that are not only made up of counting numbers, but that may include fractions, decimals, or irrational numbers, are called quantitative continuous data.
        
        E.g If you count the number of phone calls you receive for each day of the week, you might get values such as zero, one, two, or three
        
        Continuous data are often the results of measurements like lengths, weights, or times.
- - - - Stratified sample
        
        divide the population into groups called strata and then take a proportionate number from each stratum.
      - Simple random sampling
        
        Any group of n individuals is equally likely to be chosen as any other group of n individuals if the simple random sampling technique is used. In other words, each sample of the same size has an equal chance of being selected.
      - Systematic sample
        
        randomly select a starting point and take every nth piece of data from a listing of the population.
      - Cluster sample
        
        divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample.
    - - Convenience sampling that involves using results which are readily available
      - True random sampling is done with replacement
        
        That is, once a member is picked, that member goes back into the population and thus may be chosen more than once.
        
        However for practical reasons, in most populations, simple random sampling is done without replacement e.g surveys
- - - - A sample must be representative of the population. A sample that is not representative of the population is biased. Biased samples that are not representative of the population give results that are inaccurate and not valid.
    - - Responses only by people who choose to respond, such as call-in surveys, are often unreliable.
    - - Samples that are too small may be unreliable. Larger samples are better, if possible. In some situations, having small samples is unavoidable and can still be used to draw conclusions
    - - collecting data or asking questions in a way that influences the response
    - - The collected responses may no longer be representative of the population. Often, people with strong positive or negative opinions may answer surveys, which can affect the results.
    - - A relationship between two variables does not mean that one causes the other to occur. They may be related (correlated) because of their relationship through a different variable.
    - - A study performed by a person or organization in order to support their claim. Is the study impartial? Read the study carefully to evaluate the work. Do not automatically assume that the study is good, but do not automatically assume the study is bad either. Evaluate it on its merits and the work done.
    - - improperly displayed graphs, incomplete data, or lack of context
    - - When the effects of multiple factors on a response cannot be separated. Confounding makes it difficult or impossible to draw valid conclusions about the effect of each factor.