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Demand and quantity sold is an example of positive correlation. As the number of people in demand of a product increases, the quantity sold of that product also increases.

Q: Which example represents a positive correlation?

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positive correlation-negative correlation and no correlation

You can find examples by typing it in to Google. Weak positive correlation is a set of points on a graph that are loosely set around the line of best fit. The line will be positive rising up from left to right. A weak correlation can vary a lot as long as you can decipher which direction the data tends towards you have a correlation. If the points are close to the line of best fit you have a strong correlation and with a set of points perfectly lined up is perfect correlation. All three types can positive negative or perfect.

Positive Correlation

The correlation can be anything between +1 (strong positive correlation), passing through zero (no correlation), to -1 (strong negative correlation).

A positive correlation between two variables means that there is a direct correlation between the variables. As one variable increases, the other variable will also increase.

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A positive value for a correlation indicates a positive correlation; e.g. it has a positive slope.

A positive correlation.

Positive Correlation- Age - Amount of medical conditions Negative Correlation- Television Watching- Grades No Correlation- Height of a person- Number of shoes they own Hope this was helpful!

The number of pounds increases as the number of calories consumed increases.

Positive correlation = positive association Negative correlation = negative association

Positive correlation has a positive slope and negative correlation has a negative slope.

The possible range of correlation coefficients depends on the type of correlation being measured. Here are the types for the most common correlation coefficients: Pearson Correlation Coefficient (r) Spearman's Rank Correlation Coefficient (ρ) Kendall's Rank Correlation Coefficient (τ) All of these correlation coefficients ranges from -1 to +1. In all the three cases, -1 represents negative correlation, 0 represents no correlation, and +1 represents positive correlation. It's important to note that correlation coefficients only measure the strength and direction of a linear relationship between variables. They do not capture non-linear relationships or establish causation. For better understanding of correlation analysis, you can get professional help from online platforms like SPSS-Tutor, Silverlake Consult, etc.

positive correlation-negative correlation and no correlation

You can find examples by typing it in to Google. Weak positive correlation is a set of points on a graph that are loosely set around the line of best fit. The line will be positive rising up from left to right. A weak correlation can vary a lot as long as you can decipher which direction the data tends towards you have a correlation. If the points are close to the line of best fit you have a strong correlation and with a set of points perfectly lined up is perfect correlation. All three types can positive negative or perfect.

Positive correlation.Positive correlation.Positive correlation.Positive correlation.

No, the height of an NBA player in relationship to his shoe size does not represent a negative correlation. The two actually represent a positive correlation. As the NBA player increases in size, so will his shoe size.