Heritage Quest Online - US Census Records from Proquest

Heritage Quest Online - US Census Records from Proquest Available free through subscribing libraries, Heritage Quest Online packs in an intuitive interface, fast downloads, and crisp census images. If your library doesnt subscribe, youre missing out! Pros Free to members of subscribing librariesEasy to use interface and crisp, enhanced imagesNotebook feature helps you keep track of searches Cons Not available for an individual subscriptionNo soundex or wildcard search optionsHead of household indexes only Description Includes census images for all decades 1790 to 1930.Head of household indexes for 1790 to 1820, 1860, 1870, 1890, 1900 to 1910 and 1920 to 1930 (partial).Available only as a library subscription, but offered free by participating libraries to members.Advanced search options also include state, county, age, and birthplace, but no wildcard or soundex.Census indexes prepared by Heritage Quest are much more accurate than the common AIS indexes.Images appear in an HTML viewer, with no extra software required.Full-screen, enhanced census images load quickly and are easy to read.Black and white enhanced census images make viewing easier, but could possibly affect quality.Census images are also available as negative images as an alternate opportunity for readability.Handy notebook feature allows you to save census images and citations, and take online notes. Guide Review Developed specifically for library patrons, Heritage Quest Online offers an intuitive, easy-to-use interface and clear, crisp census images. Searching is simple and offers a lot of options, although it lacks the ability to use wildcards or soundex to search for misspelled names. Available census indexes are highly accurate - much more so than commonly used AIS indexes. Census images download quickly and appear as full-screen, enhanced images, though some people claim that this enhancement could introduce errors. Images can be quickly downloaded and saved or printed in Tiff (non-compressed) or PDF format. Overall, Heritage Quest Online is the most flexible census offering available, if you can convince your library to subscribe!

An Introduction to the Interquartile Range

An Introduction to the Interquartile Range The interquartile range (IQR) is the difference between the first quartile and third quartile. The formula for this is: IQR Q3 - Q1 There are many measurements of the variability of a set of data. Both the range and standard deviation tell us how spread out our data is. The problem with these descriptive statistics is that they are quite sensitive to outliers. A measurement of the spread of a dataset that is more resistant to the presence of outliers is the interquartile range. Definition of Interquartile Range As seen above, the interquartile range is built upon the calculation of other statistics. Before determining the interquartile range, we first need to know the values of the first quartile and third quartile. (Of course, the first and third quartiles depend upon the value of the median). Once we have determined the values of the first and third quartiles, the interquartile range is very easy to calculate. All that we have to do is to subtract the first quartile from the third quartile. This explains the use of the term interquartile range for this statistic. Example To see an example of the calculation of an interquartile range, we will consider the set of data: 2, 3, 3, 4, 5, 6, 6, 7, 8, 8, 8, 9. The five number summary for this set of data is: Minimum of 2First quartile of 3.5Median of 6Third quartile of 8Maximum of 9 Thus we see that the interquartile range is 8 – 3.5 4.5. The Significance of the Interquartile Range The range gives us a measurement of how spread out the entirety of our data set is. The interquartile range, which tells us how far apart the first and third quartile are, indicates how spread out the middle 50% of our set of data is. Resistance to Outliers The primary advantage of using the interquartile range rather than the range for the measurement of the spread of a data set is that the interquartile range is not sensitive to outliers. To see this, we will look at an example. From the set of data above we have an interquartile range of 3.5, a range of 9 – 2 7 and a standard deviation of 2.34. If we replace the highest value of 9 with an extreme outlier of 100, then the standard deviation becomes 27.37 and the range is 98. Even though we have quite drastic shifts of these values, the first and third quartiles are unaffected and thus the interquartile range does not change. Use of the Interquartile Range Besides being a less sensitive measure of the spread of a data set, the interquartile range has another important use. Due to its resistance to outliers, the interquartile range is useful in identifying when a value is an outlier. The interquartile range rule is what informs us whether we have a mild or strong outlier.  To look for an outlier, we must look below the first quartile or above the third quartile.  How far we should go depends upon the value of the interquartile range.