How many clusters? An information theoretic perspective.
... recently because of new areas of application, such as data mining, image and speech processing, and bioinformatics. In particular, many groups have used clustering methods to analyze the results of genome-wide expression experiments, hoping to discover genes with related functions as members of the ...
... recently because of new areas of application, such as data mining, image and speech processing, and bioinformatics. In particular, many groups have used clustering methods to analyze the results of genome-wide expression experiments, hoping to discover genes with related functions as members of the ...
Medication Adherence in Cardiovascular Disease: Generalized Estimating Equations in SAS®
... adherent or non-adherent, and there are multiple independent variables of interest. However, in this example there are multiple periods collected on each individual. One assumption of GLMs is that the residuals are independent of one another, which is not the case in this study. This repeated time m ...
... adherent or non-adherent, and there are multiple independent variables of interest. However, in this example there are multiple periods collected on each individual. One assumption of GLMs is that the residuals are independent of one another, which is not the case in this study. This repeated time m ...
Some Data on Mathematics Education
... If students can’t make their own connections with a concept as simple as the slope of a line, they won’t be able to create meaningful interpretations and connections on their own for more sophisticated mathematical concepts. For instance, • What is the significance of the base (growth or decay facto ...
... If students can’t make their own connections with a concept as simple as the slope of a line, they won’t be able to create meaningful interpretations and connections on their own for more sophisticated mathematical concepts. For instance, • What is the significance of the base (growth or decay facto ...
Math 1040 Class Skittles Proportions
... all the individual students’ candy counts by color and compiled the data into a chart. We then used this data for learning different types of statistical analysis. We made charts, graphs, and confidence intervals. This project really changed the way I think about information put out by market resear ...
... all the individual students’ candy counts by color and compiled the data into a chart. We then used this data for learning different types of statistical analysis. We made charts, graphs, and confidence intervals. This project really changed the way I think about information put out by market resear ...
Investigation #1: ES25 Student`s Water Consumption
... What proportion of students used greater than or equal to120 gallons of water per day? Explain how you got your answer (which histogram did you use, did you have to add numbers up, did you compare areas, etc.) What percentage of students consume less water than the mean (you may have to calculat ...
... What proportion of students used greater than or equal to120 gallons of water per day? Explain how you got your answer (which histogram did you use, did you have to add numbers up, did you compare areas, etc.) What percentage of students consume less water than the mean (you may have to calculat ...
Simple Linear Regression and Correlation
... The set of pairs (x, y) for which y = β0 + β1x determines a straight line with slope β1 and y-intercept β0. The objective of this section is to develop an equivalent linear probabilistic model. If the two variables are probabilistically related, then for a fixed value of x, there is uncertainty in t ...
... The set of pairs (x, y) for which y = β0 + β1x determines a straight line with slope β1 and y-intercept β0. The objective of this section is to develop an equivalent linear probabilistic model. If the two variables are probabilistically related, then for a fixed value of x, there is uncertainty in t ...
Section 4 powerpoint
... The deviations from the mean are themselves a data set, which we would like to summarize. One way would be to average them, but if we do that, the negative deviations and the positive deviations will always cancel each other out so that we end up with an average of 0. This, of course, makes the aver ...
... The deviations from the mean are themselves a data set, which we would like to summarize. One way would be to average them, but if we do that, the negative deviations and the positive deviations will always cancel each other out so that we end up with an average of 0. This, of course, makes the aver ...
On the Degree of Openness of an Open Economy
... Advantage, that is, the determination of trade patterns. Ricardo focused on relative cost differences based on technology, whereas the conventional Heckscher-Ohlin model shows that even with identical technologies and constant returns, relative costs can differ if factor proportions differ. Other au ...
... Advantage, that is, the determination of trade patterns. Ricardo focused on relative cost differences based on technology, whereas the conventional Heckscher-Ohlin model shows that even with identical technologies and constant returns, relative costs can differ if factor proportions differ. Other au ...
Time series
A time series is a sequence of data points, typically consisting of successive measurements made over a time interval. Examples of time series are ocean tides, counts of sunspots, and the daily closing value of the Dow Jones Industrial Average. Time series are very frequently plotted via line charts. Time series are used in statistics, signal processing, pattern recognition, econometrics, mathematical finance, weather forecasting, intelligent transport and trajectory forecasting, earthquake prediction, electroencephalography, control engineering, astronomy, communications engineering, and largely in any domain of applied science and engineering which involves temporal measurements.Time series analysis comprises methods for analyzing time series data in order to extract meaningful statistics and other characteristics of the data. Time series forecasting is the use of a model to predict future values based on previously observed values. While regression analysis is often employed in such a way as to test theories that the current values of one or more independent time series affect the current value of another time series, this type of analysis of time series is not called ""time series analysis"", which focuses on comparing values of a single time series or multiple dependent time series at different points in time.Time series data have a natural temporal ordering. This makes time series analysis distinct from cross-sectional studies, in which there is no natural ordering of the observations (e.g. explaining people's wages by reference to their respective education levels, where the individuals' data could be entered in any order). Time series analysis is also distinct from spatial data analysis where the observations typically relate to geographical locations (e.g. accounting for house prices by the location as well as the intrinsic characteristics of the houses). A stochastic model for a time series will generally reflect the fact that observations close together in time will be more closely related than observations further apart. In addition, time series models will often make use of the natural one-way ordering of time so that values for a given period will be expressed as deriving in some way from past values, rather than from future values (see time reversibility.)Time series analysis can be applied to real-valued, continuous data, discrete numeric data, or discrete symbolic data (i.e. sequences of characters, such as letters and words in the English language.).