a mean or a proportion) probably falls between a range of values, with a particular level of confidence (usually 95% or 99%). See here for more about sampling.)Ĭonfidence Intervals are one kind of estimation that allows us to assess where a population parameter (e.g. (Note that calculating confidence intervals ONLY makes sense if you have a random sample, do not do this if you have a non-probabilistic sample. Because we cannot know precisely what is happening with a population, we can only make our best informed assessments from what we know of our random sample. To see that, we would need to use a timeplot or simply a table.Statistical estimation is the technique of making inferences (or estimates) about a population based on sample data. There is no way to tell which temperatures are from which dates. (f) On what dates was the high temperature over 70☏?Īnother question where it would be interesting to know the answer! Unfortunately, this is another case where some information is “lost” when making a boxplot. We would need to see a dotplot or a stemplot (or the data set itself) to be able to answer this question. There is no way to answer this question with a boxplot. Information about individual data values isn’t shown. This question illustrates one weakness of a boxplot a weakness that is shared with histograms. (e) How many days in May did Anchorage see a high temperature of 65? The median high temperature in May was about 64☏. The median for this data set is between 62.5☏ and 65☏, and a bit closer to 65☏ than not. This may not always be in the middle – it depends on the shape of the distribution among other things. The median is shown by the line inside the box of the boxplot. (d) What was the median high temperature in May? So we can write: About 25% of days in May had high temperatures warmer than about 66☏. It looks like the third quartile is about 66°. Now to actually answer the question! “Complete the sentence: “About 25% of days in May had high temperatures warmer than about _ ☏.” The third quartile is what we need to complete this sentence. Third quartile – Q 3 – about 75% of a data set is smaller than the third quartile and about 25% is above.First quartile – Q 1 – about 25% of a data set is smaller than the first quartile and about 75% is above.When the data set is placed in order from smallest to largest, these divide the data set into quarters. You may think that we need to be able to count values in the data set to answer this question, but actually we don’t! This is a question that can be answered using the fact that the boxplot shows the quartiles. (c) Complete the sentence: “About 25% of days in May had high temperatures warmer than about _ ☏.” Without the actual data set, we will often have to estimate. That is, we won’t always be able to give an exact answer from the graph depending on the scale. This is something you should be comfortable with. The minimum looks just about 47.5°, so we will estimate it at 48° and as a final answer we can say “The lowest observed temperature in May was about 48☏.” Since every other line is labelled and it is counting by 5, the in between lines must represent 2.5°. We are looking for the minimum value here.įirst, you need to figure out the scale. Since there are no outliers, the main line through the boxplot starts at the minimum value and ends at the maximum value. (b) What was the lowest high temperature observed in May? There are no stars or other points past the main line in the boxplot, so no, there are no outliers in this data set. (a) Are there any outliers in this data set? Depending on the software used, you may see either configuration. **(f) On what dates was the high temperature over 70☏?īefore we answer these, notice that this particular boxplot is vertical instead of horizontal. **(e) How many days in May did Anchorage see a high temperature of 65? Use this to answer the following questions. The boxplot below shows the high temperatures in Anchorage, Alaska in May 2014*. So, now that we have addressed that little technical detail, let’s look at an example to see what kinds of questions we can answer using a boxplot. If there are no outliers, you simply won’t see those points. If a data set has no outliers (unusual values in the data set), a boxplot will be made up of the following values.īut, if there ARE outliers, then a boxplot will instead be made up of the following values.Īs you can see above, outliers (if there are any) will be shown by stars or points off the main plot.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |