The weight Lucy lost with respect to number of weeks was recorded for six weeks. The correlation coefficient was calculated to be r = 0.0502. Interpret the meaning of the correlation coefficient in terms of the scenario. There is a weak, negative correlation between the weight Lucy lost and the number of weeks.
There is no correlation between the weight Lucy lost and the number of weeks.
There is a strong, positive correlation between the weight Lucy lost and the number of weeks.
There is a weak, positive correlation between the weight Lucy lost and the number of weeks.
There is a strong, negative correlation between the weight Lucy lost and the number of weeks.

There is a weak, positive correlation between the weight Lucy lost and the number of weeks.

Explanation:

The correlation coefficient is used to measure the relationship between two variables in terms of how they move in relation to one another.

If two variables are said to have a positive correlation, it means that they increase at the same time and decrease at the same time for example, there is a positive correlation between the amount of food a family buys and how much money they have because the more money they have, the more food they buy.

Negative correlations are the reverse for instance Ice cream sales and cold temperatures. The colder it is, the less people buy ice cream.

The Correlation coefficient ranges from -1 to +1 with +1 (-1) meaning that the variables are perfectly positively(negatively) correlated. The closer the value is to 0, the weaker the correlation.

Generally, for a correlation coefficient between the numbers 0 and +0.3, there is a weak positive correlation.

With a correlation coefficient of 0.0502, there is therefore a weak, positive correlation between the weight Lucy lost and the number of weeks.

answer: all of the above

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