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What else can I help you with?
What kind of research is needed to identify relationships between variables but does not determine cause and effect?
Correlation. It will merely determine whether or not there is a linear relationship between the variables. However, the absence of correlation is not absence of a relation - only that the relationship is not linear.For example, if you take any set of points that are symmetrically placed about a vertical axis - such as from a circle, ellipse or parabola, or parts of a sine or cosine curve - then the correlation will be 0. But, the fact that these are well-defined curves clearly implies a very definite [non-linear] relationship.
Can period affect a girls height?
A woman's period does not affect her height. Her height is affected by the genetics of her family which will determine how tall she grows.
Correlation between eye color and height?
there is none.
Is there a correlation between high tide and moon rise?
yes there is a correlation between high tide and moon rise because the higher the moon gets in the sky the higher the tide will be.
Statical messure of the extent in which two factors vary together?
covariance or correlation
When an experiment shows that two variable are closely related that experiment shows?
that there is a correlation between the two variables. However, correlation does not imply causation, so it is important to further investigate to determine the nature of the relationship between the variables.
What is faunal correlation?
Faunal Cross-correlation is the use of animal bones found within an archaeological site to determine a relative date.
What is the significance of correlation time in the context of statistical analysis?
In statistical analysis, correlation time is important because it measures how long it takes for two variables to become independent of each other. It helps determine the strength and stability of relationships between variables over time.
What does correlation mean in maths?
Correlation is a statistical measure of the linear association between two variables. It is important to remember that correlation does not mean causation and also that the absence of correlation does not mean the two variables are unrelated.
What is correlation What are the different types of correlation Why is it important to determine correlation What does it mean when it is said that two variables have no correlation?
A correlation is the relationship between two or more variables. Correlations are described as either weak or strong, and positive or negative. There can be a perfect correlation between variables, or no correlation between variables. It is important to determine the correlation between variables in order to know if and how closely changes in one variable are reflected by changes in another variable. This is done by determining the coefficient of correlation (r), which describes the strength of the relationship between variables and the direction. -1 ≤ r ≤ +1 if r= +1 or -1, there is a perfect correlation if r= 0 there is no correlation between the variables. a value closer to + or - 1 demonstrates a strong correlation, while a value closer to 0 demonstrates a weak correlation. a + value demonstrates that when one variable increases the other variable increases, while a - value demonstrates that when one variable increases the other variable decreases. However, it is very important to understand that correlation is not the same as relationship. Consider the two variables, x and y such that y = x2 where x lies between -a and +a. There is a clear and well-defined relationship between x and y, but the correlation coefficient r is 0. This is true of any pair of variables whose graph is symmetric about one axis. Conversely, a high correlation coefficient does not mean a strong relationship - at least, not a strong causal relationship. There is pretty strong correlation between my age and [the log of] the number of television sets in the world. That is not because TV makes me grow old nor that my ageing produces TVs. The reason is that both variables are related to the passage of time.
Explain how you can determine the type of correlation for a set of data pairs by examining the data in a table without drawing a scatter plot?
"If y tends to increase as x increases, then the data have a positive correlation. If y tends to decrease as x increases, then the data have a negative correlation. If the points show no correlation, then the data have approximately no correlation."
What type of correlation does the scatter graph show?
To determine the type of correlation shown in a scatter graph, you would typically look at the pattern of the plotted points. If the points trend upwards from left to right, it indicates a positive correlation. Conversely, if the points trend downwards, it suggests a negative correlation. If the points are scattered without any discernible pattern, it indicates little to no correlation.
How can statistic determine the relationship between two phenomena?
Statistics can determine the relationship between two phenomena by using correlation and regression analysis. Correlation measures the strength and direction of a relationship between two variables, while regression analysis helps in understanding how the dependent variable changes as the independent variable varies. By analyzing data and identifying patterns, statisticians can infer potential causal relationships and make predictions. However, it's important to note that correlation does not imply causation, necessitating careful interpretation of results.
What type of correlation on a graph would there be for the color of a persons hair and their weight?
There would be no definite correlation. It would just be a random correlation that would be all over the graph because there is no trend in hair color and weight. Your weight doesn't determine your hair color.
What is the goal of correlation?
The goal of correlation is to measure the strength and direction of the relationship between two variables. It helps to determine whether changes in one variable are associated with changes in another, without implying causation. Correlation is often quantified using the correlation coefficient, which ranges from -1 to 1, indicating the degree of linear relationship. Understanding correlation can aid in predictive modeling and data analysis in various fields.
Is there a correlation between webinar and reduced car pollution?
I don't know if there is a direct correlation but if people are using a webinar instead of traveling to a lecture hall, it could theoretically reduce car pollution levels. Some studies would need to be conducted to determine the exact correlation of this.
What type of research could allow you to determine whether students' grades accurately predict later income?
Correlation
