Statistics

Statistics

1. Data

   • Consist of information coming from observations, counts, measurements, or responses.
   • Data Classification
     • Qualitative
       • Consist of attributes, labels, or nonnumerical data
       • Nominal
         • Categorized using, names, labels, or qualities. No mathematical computations at be made at this level.
       • Ordinal
         • is qualitative or quantitative. Data can be arranged in order, or ranked, but differences between data entries are not meaningful.
     • Quantitative
       • Consist of numerical measurements or counts.
       • Interval
         • Can be ordered, and meaningful differences between data entries can be calculated. A zero entry simply represents a position on a scale; the entry is not a not an inherent zero.
       • Ratio
         • A zero entry is an inherent zero. A ratio between 2 data values can be formed so that one data value can be meaningfully expressed as a multiple of another. Data is meaningful!
   • Data Collection
     • Observational Study
       • A researcher observes and measures characteristics of interest of part of a population but doesn't change existing conditions. 
     • Experiment
       • A treatment is applied to a part of a population and responses are observed. 
       • Control Group
         • Part of the population is given no treatment aka "Placebo" which is a fake treatment. 
     • Simulation
       • Using a mathematical or physical model to reproduce the conditions of a situation or process. Often you have to use computers to simulate situations that would be to difficult to do in real life. Then you take the data from that 
     • Survey
       • Is an investigation of one or more characteristics of a population.  Survey is done making questions that don't lead to biased answers.
   • Experimental Design
     • Confounding Variable
       • Means two or more things could be effecting a certain outcome. 
     • Blinding
       • Where subjects don't know if they are receiving a treatment or placebo
       • Double-Blind
     • Randomization
       • Assigning subjects to different treatment groups.
       • Randomized block design
         • Divide subjects with similar characteristics into blocks, and then, within each block, randomly assign subjects to treatment groups. 
     • Replication
       • Is repeating an experiment under the same or similar conditions to get a better outcome.

2. Population

   • is the collection of all outcomes, responses, measurements, or counts that are of interest.
   • Parameter
     • A numerical description of a population characteristic
   • Census
     • Count or measure of the entire population

3. Sample

   • is a subset, or parrt, of a population
   • statistic
     • a numerical description of a sample characteristic.
   • Sampling Techniques
     • Random Sample
       • Every member of population has an equal chance of being selected.
       • Simple Random Sample
         • Every possible sample size has the same chance of being selected.  Assign numbers to the each member of the sample size.
     • Stratified Sample
       • Samples members of each segment of the population.  Members are divided into 2 or more subsets called STRATA. They share same characteristics. Then a sample is randomly selected.  
     • Cluster Sample
       • When population already is naturally divided into subsets they are called clusters. select all members in one or more but NOT all
     • Systematic Sample
       • Members are assigned numbers. then they are ordered in some way. For example, every 10th person in a line.  
     • Conveniece Sample
       • Is a sample that leads to biased outcomes. only consist of available members of the population.

4. Descriptive statistics

   • Is the branch of statistics that involves the organization, summarization, and display of data. 

5. Inferential statistics

   • is the branch of statistics that involves using a sample to draw conclusions about a population. 
   • probability