This can provide an assessment of "goodness of fit" that is graphical, rather than reducing to a numerical summary. Q–Q plots are commonly used to compare a data set to a theoretical model. A Q–Q plot is generally a more powerful approach to do this than the common technique of comparing histograms of the two samples, but requires more skill to interpret. The use of Q–Q plots to compare two samples of data can be viewed as a non-parametric approach to comparing their underlying distributions. Q–Q plots can be used to compare collections of data, or theoretical distributions.
Q–Q plots can also be used as a graphical means of estimating parameters in a location-scale family of distributions.Ī Q–Q plot is used to compare the shapes of distributions, providing a graphical view of how properties such as location, scale, and skewness are similar or different in the two distributions. If the distributions are linearly related, the points in the Q–Q plot will approximately lie on a line, but not necessarily on the line y = x. If the two distributions being compared are similar, the points in the Q–Q plot will approximately lie on the line y = x. Thus the line is a parametric curve with the parameter which is the number of the interval for the quantile. A point ( x, y) on the plot corresponds to one of the quantiles of the second distribution ( y-coordinate) plotted against the same quantile of the first distribution ( x-coordinate). First, the set of intervals for the quantiles is chosen. In statistics, a Q–Q (quantile-quantile) plot is a probability plot, which is a graphical method for comparing two probability distributions by plotting their quantiles against each other. The curved pattern suggests that the central quantiles are more closely spaced in July than in March, and that the July distribution is skewed to the left compared to the March distribution. PAST PERFORMANCE IS NOT INDICATIVE OF FUTURE RESULTS.A Q–Q plot comparing the distributions of standardized daily maximum temperatures at 25 stations in the US state of Ohio in March and in July. ETF.com MAKES NO REPRESENTATIONS ABOUT THE SUITABILITY OF THE INFORMATION, PRODUCTS OR SERVICES CONTAINED HEREIN. You should not use such information for purposes of any actual transaction without consulting an investment or tax professional.ĮTF.com DOES NOT TAKE RESPONSIBILITY FOR YOUR INVESTMENT OR OTHER ACTIONS NOR SHALL ETF.com HAVE ANY LIABILITY, CONTINGENT OR OTHERWISE, FOR THE ACCURACY, COMPLETENESS, TIMELINESS, OR CORRECT SEQUENCING OF ANY INFORMATION PROVIDED BY ETF.com OR FOR ANY DECISION MADE OR ACTION TAKEN BY YOU IN RELIANCE UPON SUCH INFORMATION OR ETF.com. A reference to a particular investment or security, a credit rating, or any observation concerning a security or investment provided in the ETF.com Service is not a recommendation to buy, sell, or hold such investment or security or to make any other investment decisions. The data and information contained herein is not intended to be investment or tax advice.
The fund and index are rebalanced quarterly and reconstituted annually. In all, QQQ delivers a quirky but wildly popular mash-up of tech, growth and large-cap exposure. Still, the fund has huge name recognition for the underlying index, the NASDAQ-100. The ETF is much more concentrated in its top holdings and is more volatile than our vanilla large-cap benchmark. The fund's arcane weighting rules further distance it from anything close to plain vanilla large-cap or pure-play tech coverage. QQQ has huge tech exposure, but it is not a 'tech fund' in the pure sense either. Per the rules of its index, the fund only invests in nonfinancial stocks listed on NASDAQ, and effectively ignores other sectors too, causing it to skew massively away from a broad-based large-cap portfolio. The product is one of a few ETFs structured as a unit investment trust. Often referred to as “the triple Q’s”, it's also one of the most unusual. QQQ is one of the best established and typically one of the most actively traded ETFs in the world. QQQ tracks a modified-market-cap-weighted index of 100 NASDAQ-listed stocks.
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