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Which graph is most is most useful for making predictions about dependent variables?
line graph
What else can I help you with?
When is a bar graph useful?
when a sets of data can be separated by 2 orders of variables, which are the independent & dependent variables.
How can a line of best fit be useful?
It is very useful and interesting to be able to enter data for two variables, graph those points in a scatter plot, and then generate a line of best fit through those points. From the line of best fit, it is fairly simple to generate a linear equation. A line of best fit is drawn through a scatterplot to find the direction of an association between two variables. This line of best fit can then be used to make predictions.
Explain why bar graphs are useful for comparing data?
so you know the relationship between the 2 variables
What is the difference between correlation analysis and?
Correlation analysis is a type of statistical analysis used to measure the strength of the relationship between two variables. It is used to determine whether there is a cause-and-effect relationship between two variables or if one of the variables is simply related to the other. It is usually expressed as a correlation coefficient a number between -1 and 1. A positive correlation coefficient means that the variables move in the same direction while a negative correlation coefficient means they move in opposite directions.Regression analysis is a type of statistical analysis used to predict the value of one variable based on the value of another. This type of analysis is used to determine the relationship between two or more variables and to determine the direction strength and form of the relationship. Regression analysis is useful for predicting future values of the dependent variable given a set of independent variables.Correlation Analysis is used to measure the strength of the relationship between two variables.Regression Analysis is used to predict the value of one variable based on the value of another.
What is the limitation of pie chart?
A pie chart is useful for between 3 and 7 or 8 segments. With more segments it becomes difficult to use. A pie chart is useful for looking at the breakdown, into parts, of a single total. It is not very good for comparing the breakdowns of two (or more) variables: for example, budgets headings for two years. This is because many people confuse the fact that a circle of double the radius would represent a quadrupling of the total. This quadratic relationship is often used to misrepresent data.
What type is most useful for making predictions about predictions about dependent variables?
Data tabel
Which type of graph is most useful for making predictions dependent variables?
line graph
Which type graph of graph is most useful for making predictions about dependent variables?
line graph
What type of graph is most useful for making predictions about dependent variables?
A regression graph is most useful for predicting dependent variables, as it shows the relationship between the independent and dependent variables, allowing for the prediction of future values.
When this is strong can be useful for making predictions?
i believe the answer is.... A strong OBSERVATION can be useful for making predictions
What are generalizations that are useful in making predictions based on data?
Predictions
When is a bar graph useful?
when a sets of data can be separated by 2 orders of variables, which are the independent & dependent variables.
Which graph is most useful for showing how the relationship between independent and dependent variables changes over time?
Time Series.
Summarize how the periodic table is organized and tell this organization is useful?
The number of electrons an element has determine the organization. This table helps in making predictions about how an element will chemically react.
What variables are useful for two-way communication between modules?
Constant Variables
What is ex-post-facto design?
Ex Post Facto (also called Causal Comparative Research) is useful whenever: • We have two groups which differ on an independent variable and we want to test hypotheses about differences on one or more dependent variables OR • We have two groups which already differ on a dependent variable and we want to test hypotheses about differences on one or more independent variables
What is ex-post facto design?
Ex Post Facto (also called Causal Comparative Research) is useful whenever: • We have two groups which differ on an independent variable and we want to test hypotheses about differences on one or more dependent variables OR • We have two groups which already differ on a dependent variable and we want to test hypotheses about differences on one or more independent variables
