Watch More! Unlock the full videos with a FREE trial
Included In This Lesson
Access More! View the full outline and transcript with a FREE trial
Transcript
Today we’re going to be talking about interpreting trends.
So many times that we collect data we do so in order to understand what might be happening a certain time or to see what happens over time. We graph data to look for Trends that give us an idea of an underlying pattern. Like here is a graph generated by Google Trends on the number of Google searches worldwide for the term flu from Dec 2018 to Dec 2019. We can look for trends and possibly infer from this data.
Shifts in data can happen when a constant is added across the board (to each data point). When this happens this will shift the value of the mean and mode. A typical shift will not change the standard deviation, variance or percent values however. So a good example of this would be if you were looking at say the weights of various items that are approximately the same sie and can use the same box for shipping. If that same box suddenly was changed to a heavier version. The values would shift. This would increase the mean and mode but the data’s STD dev, variance and % values would not be affected.
Positive trends in data show a relationship between X & Y . As one value increases so to does the other. Like exercise and heart rate. Negative trends are opposing. As one value increases the other decreases. Like for example exercise and BMI.
We can graph data and understand whether a trend is positive or negative by creating a line of regression/ trend line. This is a line of best fit between the data set that shows a relationship between the x and y values.
And from that line we can also extrapolate and estimate from the trend line what the values would be beyond that which was collected. This is usually represented with a dotted/dash line extending from the trend line.
So in summary, trends tell us if there is a change.
Shifts affect the mean and mode of data but not std dev or percent values.
Trends tend to show positive or negative correlation.
And a line of regression helps how relationships between the x & y values that we can then infer beyond that best fit line.
We love you guys! Go out and be your best self today! And as always, Happy Nursing!
View the FULL Transcript
When you start a FREE trial you gain access to the full outline as well as:
- SIMCLEX (NCLEX Simulator)
- 6,500+ Practice NCLEX Questions
- 2,000+ HD Videos
- 300+ Nursing Cheatsheets
“Would suggest to all nursing students . . . Guaranteed to ease the stress!”
