Expressions that simlify to the same expression are called
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A statement which best describes the strength of the correlation, and the causation between the variables is that: D. it is a strong positive correlation, and it is likely causal.
<h3>What is a positive correlation?</h3>A positive correlation can be defined as a terminology that is used to described a scenario (situation) in which two variables move in the same direction and are in tandem.
This ultimately implies that, a positive correlation exist when two variables have a linear relationship or are in direct proportion. Hence, when one variable increases, the other increases as well, and vice-versa.
By critically observing the scatter plot (see attachment) which models the data in the given table, we can infer and logically deduce that the value on the y-axis (circumference) increases as the value on the x-axis (radius) increases, so this is a strong positive correlation.
Also, we know that there exist a direct relationship between the circumference of a circle and its radius, so this relationship is most likely causal.
In conclusion, a statement which best describes the strength of the correlation, and the causation between the variables is that it's a strong positive correlation, and it is likely causal.
Read more on positive correlation here: brainly.com/question/10644261
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Using margin of error, it is found that increasing the sample size results in a smaller sampling error.
The equation for the <em>margin of error</em> is given by:
In which:
- c is the critical value according to the distribution used.
- s is the standard deviation, either of the sample or of the population.
- n is the sample size.
From the equation, it can be noted that the margin of error is inversely proportional to the square root of the sample size, hence, increasing the sample size results in a smaller sampling error.
To learn more about margin of error, you can take a look at brainly.com/question/25821952