Answers:
- Negative
- Positive
- Strong Positive
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Step-by-step explanation:
We'll focus on the plot at the very left. The dots seem randomly scattered about, but they seem to go downhill as we move from left to right. I would consider this fairly weak negative correlation since the points aren't anywhere close to the same single straight line (known as the regression line or line of best fit), but again they seem to trend downhill in some fashion. Since "weak negative" isn't an answer choice, I'd go with "negative".
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Now move to the scatterplot in the middle. We have the points trending upward as we move from left to right. I'd consider this weak positive correlation for similar reasoning as discussed in the previous section. Since "weak positive" isn't listed, I would go with "positive" as the next best thing.
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Lastly, the third plot has similar properties to the second one. Though the points are now more clumped together around where the regression line would go. You can think of the regression line as a magnet that is pulling in the points. We don't have a perfect positive correlation, or else all the points would lay on the same line and there wouldn't be any straggler/outlier points that are off the line. I would consider this to be strong positive correlation.
Unfortunately the distinction between "strong positive" and "very strong positive" is too vague. Your teacher hasn't defined where the cutoff line is between each. I'm going with "strong" over "very strong" because the points seem to have a bit more wiggle room to get closer to the line, yet still not be considered perfectly on the line. Again this is all subjective and will be a matter of opinion. Without a ruleset and hard numbers, it's impossible to answer this accurately. The same can be said about the previous two sections, but I don't think there's as much ambiguity there.