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What correlation results when there is no relationship between two variables?
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Distinguish between correlation and regression?
Correlation is a measure of the degree of agreement in the changes (variances) in two or more variables. In the case of two variables, if one of them increases by the same amount for a unit increase in the other, then the correlation coefficient is +1. If one of them decreases by the same amount for a unit increase in the other, then the correlation coefficient is -1. Lesser agreement results in an intermediate value. Regression involves estimating or quantifying this relationship. It is very important to remember that correlation and regression measure only the linear relationship between variables. A symmetrical relationshup, for example, y = x2 between values of x with equal magnitudes (-a < x < a), has a correlation coefficient of 0, and the regression line will be a horizontal line. Also, a relationship found using correlation or regression need not be causal.
If doubling the manipulating variable results in a doubling of the responding variable the relationship between the variables is a?
This would indicate that there is a linear relationship between manipulating and responding variables.
What is the difference between manipulated variables and controlled variables?
They are the same. These are names for the variables in an experiment that are controlled by the experimenter, as opposed to the output variables, the results you collect at the end of the experiment Hope this helped!
How do you investigate the effect on period of a pendulum if length is altered?
You measure the period of the pendulum for different lengths. Plot the results on a scatter plot and see if you can work out the nature of the relationship between the two variables.
What third variables might there be that would cause a spurious correlation in the survey results?
The third variable could be one which is correlated to both variables. These are called confounding variable. For example, in the UK you could find a correlation between coastal air pollution and ice cream sales. This is not because eating ice cream causes air pollution nor because air pollution causes people to eat ice cream. The confounding variable is the temperature. Warm weather gets people to drive to the sea!
Distinguish between correlation and regression?
Correlation is a measure of the degree of agreement in the changes (variances) in two or more variables. In the case of two variables, if one of them increases by the same amount for a unit increase in the other, then the correlation coefficient is +1. If one of them decreases by the same amount for a unit increase in the other, then the correlation coefficient is -1. Lesser agreement results in an intermediate value. Regression involves estimating or quantifying this relationship. It is very important to remember that correlation and regression measure only the linear relationship between variables. A symmetrical relationshup, for example, y = x2 between values of x with equal magnitudes (-a < x < a), has a correlation coefficient of 0, and the regression line will be a horizontal line. Also, a relationship found using correlation or regression need not be causal.
If doubling the manipulating variable results in a doubling of the responding variable the relationship between the variables is a?
This would indicate that there is a linear relationship between manipulating and responding variables.
In an experiment if doubling the manipulated variable results in a doubling of the responding variable the relationship between the variables is a?
it is a direct relationship -eli martin
Which correlation coefficient indicates the strongest relation between two variables?
Generally speaking it is the coefficient that produces a ratio between variables of 1:1. If the variables are of a dependent/independent framework, I find that Chronbach's or Pearson's produces the most accurate (desirable) results. Hope this helps for answering a very good question for what appears to be n enthusiastic novice investigator.
Does Lamictal affect serum HCG results?
No. There is no known correlation between the two.
What is the relationship between the results and the conclushion?
The relationship between results and conclusions are that the information from the results lead a person(s) to form a conclusion.
How can I perform a correlation analysis in SPSS?
To perform a correlation analysis in SPSS, you can follow these steps: Open SPSS and load your dataset by selecting "File" and then "Open" or by using the "Open" button on the toolbar. Once your dataset is loaded, go to the "Analyze" menu at the top of the SPSS window and select "Correlate." In the submenu that appears, choose "Bivariate." In the "Bivariate Correlations" dialog box, select the variables you want to include in the correlation analysis. You can either double-click on variables to move them to the "Variables" list or use the arrow buttons. You can select multiple variables by holding down the Ctrl key (or Command key on Mac) while clicking on the variables. By default, SPSS will calculate Pearson correlation coefficients. If you want to compute other types of correlation coefficients, such as Spearman's rank correlation or Kendall's tau-b, click on the "Options" button. In the "Bivariate Correlations: Options" dialog box, select the desired correlation coefficient under "Correlation Coefficients." You can also choose to calculate p-values and confidence intervals for the correlations by checking the corresponding options in the "Bivariate Correlations: Options" dialog box. After selecting the variables and options, click the "OK" button to run the correlation analysis. SPSS will generate the correlation matrix, which displays the correlation coefficients between all pairs of variables selected for analysis. The correlation matrix will appear in the output window. To interpret the correlation results, examine the correlation coefficients. Values range from -1 to 1, where -1 indicates a perfect negative correlation, 1 indicates a perfect positive correlation, and 0 indicates no correlation. Additionally, consider the statistical significance of the correlations. If p-values were calculated, values below a certain threshold (e.g., p < 0.05) indicate statistically significant correlations. You can save the output as a file by selecting "File" and then "Save" or by using the "Save" button on the toolbar. That's how you can perform a correlation analysis in SPSS. Remember to carefully select the variables and interpret the results appropriately based on your research question or analysis objective.
When would you use simple linear regression?
You use it when the relationship between the two variables of interest is linear. That is, if a constant change in one variable is expected to be accompanied by a constant [possibly different from the first variable] change in the other variable. Note that I used the phrase "accompanied by" rather than "caused by" or "results in". There is no need for a causal relationship between the variables. A simple linear regression may also be used after the original data have been transformed in such a way that the relationship between the transformed variables is linear.
What is the difference between manipulated variables and controlled variables?
They are the same. These are names for the variables in an experiment that are controlled by the experimenter, as opposed to the output variables, the results you collect at the end of the experiment Hope this helped!
How do you investigate the effect on period of a pendulum if length is altered?
You measure the period of the pendulum for different lengths. Plot the results on a scatter plot and see if you can work out the nature of the relationship between the two variables.
How do you use correlation in a sentence?
The results of the two tests correlate to a high degree.
How does the manipulation of an independent variable during a scientific experiment allow a scientist to find a cause-and-effect relationship between variable?
The manipulation of an independent variable during a scientific experiment allows a scientist to find a cause and effect relationship between variables. This is because the manipulation changes the results and measurements.
