RESEARCH

• Data analysis - the process of systematically applying statistical and/or logical techniques to describe and illustrate, condense and recap, and evaluate data
• Bivariate analysis - allows you to investigate the relationship between two variables. it is useful to determine weather there is a correlation between the variables and, if so, how strong the connection is.
• Bivariate typically, involves X and Y are the two of the measures included. the bivariate data can be understood as a pair (X,Y).

  INDEPENDENT AND DEPENDENT VARIABLES
• most common type of bivariate analysis is SCATTERPLOTS
• TYPES OF SCATTERPLOT

  • Positive Correlation
  • Negative Correlation
  • No Correlation
• A scatterplot is a graph that shows how two variables are related to each other. it shows the values of one variable on the x-axis and the values of the other variable on the y-axis.
• Positive correlation - as one variable increases, so does the other variable increases.
• Negative correlation - as one variable increases, the other variable decreases.
• No Correlation - No relationship between the variables.
• When there is no pattern to where the points are going, then it is a no correlation scatterplot. This means that there is no relationship between the two variables
• A positive scatter plot is a graph that shows some data points that trend up from left to right in a linear fashion. This means that as x increases, so does y.
• Zero correlation means that there is no relationship between the data points.
• A negative scatter plot is a graph that shows some data points that trend up from rigth to left in a linear fashion. This means that as x increases, y decrease.
• When there is no pattern to where the points are going (how they are trending), then it is a no correlation scatterplot. This means that there is no relationship between the two variables
• A positive scatter plot is a graph that shows some data points that trend up from left to right in a linear fashion. This means that as x increases, so does y.
• A scatterplot is not the same as a correlation, but they are related. A scatterplot is the graph or the visual representation of the data. Correlation determines if there is a pattern among the data.
• A perfect positive correlation means that there is a line that can be drawn through the data points on a scatter plot. This line crosses through every point on the graph.
• What are the 3 types of scatterplots?The three types of scatterplots are the following kinds: positive correlation scatterplot (follows a positive linear function), negative association scatterplot (follows a negative linear function), and no correlation scatterplot (there is no function it can follow).
• Zero correlation means that there is no relationship between the data points. An example of this would be the amount of chocolate someone eats and how many hours they spend on homework
• These also refer to the relationship between the variables: positive means as x increases so does y, negative means as x increases y decreases, and no correlation means there is no relationship between x and y.
• When you draw a conclusion from a passage, you Put together an idea that was implied in the passage, but not stated outright 
• What do you call to the inferences or generalization that is based on the findings?

   Interpretation
• What do you call to the actions to be taken based on the findings and related to conclusion?

  Recommendation
• Scatter plots are used to look for what?

  Patterns
• Recommendation should not be Bias. What is another term for the word Bias?


  Bigotry
• For her research project, Jerri interviewed ten people asking them the same open-ended questions. What type of research did Jerri engage in?

  Qualitative Research
• In quantitative research:

  summary of findings
• In qualitative research:

  summary of results
• are inferences, abstractions (concept and idea), general statements, and/or generalizations based upon the findings.

  Conclusion
• it suggest actions to be taken based on findings.

  recommendation
• it is related to conclusion

  recommendation
• it is not based on biases or beliefs that are not supported by data

  recommendation