It tells you that if there were a linear relationship between the two variables, what that relationship would look like and also how much the observations differed from that linear fit.
It depends on which calculator! If the data is linear, you can estimate the slope of the line and the y-intercept from graphing the data. By graphing the data, you will be able to tell if it forms a straight line or not.
On a chart, such as a line chart, a data markers shows where the point is, usually done with a dot or a box or a cross. A data label will show the actual value of that data point. So on a line chart you might see a data marker on the line to indicate it is a value from the data and with it a data label will tell you what the actual value is.
A visual inspection of the scatterplot should tell you whether a straight line or a simple curve is appropriate. You could carry out an analysis of variance (ANOVA) and test the reduction in the residual sums of squares to see whether the curve is significantly better than the line. However, remember that with n observations, a curve with n-1 independent parameters (for example a polynomial of order n-1) will give a prefect fit.
It's impossible to tell unless we have both the graph and the set of data.
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It tells you if the data raised alot or little.(Ex:if the first point is x95:y5 and the second is x95:y90 it is a steep slope.)
No. Definitely not if the lines intersected near their means.
You could tell whether or not the data were skewed but that is all. You could make no assessment about the central tendency (mean) or spread (range, inter-quartile range).
The ratio of a pair of values is always the same. or The scatter plot of the data indicates a straight line with a positive slope that passes through the origin.
You usually want to use a bar graph. If you have a year of data you probably want to use a line graph.
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