Computing transformations
... each case. For each of these calculations, there may be data values which are not mathematically permissible. For example, the log of zero is not defined mathematically, division by zero is not permitted, and the square root of a negative number results in an “imaginary” value. We will usually adjus ...
... each case. For each of these calculations, there may be data values which are not mathematically permissible. For example, the log of zero is not defined mathematically, division by zero is not permitted, and the square root of a negative number results in an “imaginary” value. We will usually adjus ...
2 Describing Data- Frequency Tables, Frequency
... There is a unique median for each data set. It is not affected by extremely large or small values and is therefore a valuable measure of central tendency when such values occur. It can be computed for ratio-level, intervallevel, and ordinal-level data. It can be computed for an open-ended frequency ...
... There is a unique median for each data set. It is not affected by extremely large or small values and is therefore a valuable measure of central tendency when such values occur. It can be computed for ratio-level, intervallevel, and ordinal-level data. It can be computed for an open-ended frequency ...
2. Procedures (Ttest, NPar1Way,Freq)
... Here are the SAS symbols for comparisons and logical relations. Letters are easier to read and remember. ...
... Here are the SAS symbols for comparisons and logical relations. Letters are easier to read and remember. ...
Descriptive Statistics
... Computing the Median • To compute the median, we sort the values from low to high. The median is the middle score. • If the number of cases in the sample is an odd number, the middle case is the case above and below which the same number of cases occur. ( e.g. 1 2 3 4 5 ) ...
... Computing the Median • To compute the median, we sort the values from low to high. The median is the middle score. • If the number of cases in the sample is an odd number, the middle case is the case above and below which the same number of cases occur. ( e.g. 1 2 3 4 5 ) ...
Summarizing Data, Histograms, Scatter Plots - CEDAR
... Visualizing and Exploring Data Sargur Srihari University at Buffalo The State University of New York ...
... Visualizing and Exploring Data Sargur Srihari University at Buffalo The State University of New York ...
A simple guide to statistics - Tropical Biology Association
... Discontinuous variables/data - usually whole integers, mostly counts, or frequencies of things. Continuous data - values along a scale, usually measurements (e.g. height, mass, temperature, etc.). ...
... Discontinuous variables/data - usually whole integers, mostly counts, or frequencies of things. Continuous data - values along a scale, usually measurements (e.g. height, mass, temperature, etc.). ...
Basic statistics: a survival guide
... The area under the ‘other population’ curve (blue) to the left of our sample IQ of 107.5 represents the likelihood of observing this sample mean of 107.5 by chance under the alternative hypothesis (that the sample is from the ‘other population’) This is known as the b level and is normally set at ...
... The area under the ‘other population’ curve (blue) to the left of our sample IQ of 107.5 represents the likelihood of observing this sample mean of 107.5 by chance under the alternative hypothesis (that the sample is from the ‘other population’) This is known as the b level and is normally set at ...
SSG9 230 - public.asu.edu
... Whereas y provides an approximate measure of the average distance that Y scores fall on either side of the mean of the Y scores, y’ provides an approximate measure of the average distance that Y scores fall from their predicted scores (Y’). ...
... Whereas y provides an approximate measure of the average distance that Y scores fall on either side of the mean of the Y scores, y’ provides an approximate measure of the average distance that Y scores fall from their predicted scores (Y’). ...
statistics - summary - Michigan State University
... a. Measures of strength of a relationship vs a statistical test of a hypothesis. There are a number of statistics that measure how strong a relationship is, say between variable X and variable Y. These include parametric statistics like the Pearson Correlation coefficient, rank order correlation mea ...
... a. Measures of strength of a relationship vs a statistical test of a hypothesis. There are a number of statistics that measure how strong a relationship is, say between variable X and variable Y. These include parametric statistics like the Pearson Correlation coefficient, rank order correlation mea ...
Relating two variables: linear regression and correlation
... parameters which define its distribution, assessing the precision of the estimates and trying to decide if values of the parameters are different in separate groups. Quite often we need to consider more than one variable and how they relate to one another. The of assessing the relationship between s ...
... parameters which define its distribution, assessing the precision of the estimates and trying to decide if values of the parameters are different in separate groups. Quite often we need to consider more than one variable and how they relate to one another. The of assessing the relationship between s ...
Basic statistics using R
... ¾ Examine Hygrometer dataset. Notice that the measuments were taken on two different dates (day1 and day2 – each hygrometer was read before and after a few rainy days). ¾ Modify the dataset so that the order of the measurements is retained, but the measurements for the day1 and day2 are in two separ ...
... ¾ Examine Hygrometer dataset. Notice that the measuments were taken on two different dates (day1 and day2 – each hygrometer was read before and after a few rainy days). ¾ Modify the dataset so that the order of the measurements is retained, but the measurements for the day1 and day2 are in two separ ...
StatCalc User Manual
... Used to test for the difference between one population mean (mu) and one sample mean. Enter the population mean, sample mean, sample (or population) standard deviation and the number of observations in the sa ...
... Used to test for the difference between one population mean (mu) and one sample mean. Enter the population mean, sample mean, sample (or population) standard deviation and the number of observations in the sa ...
R Commander an introduction
... Categorical variables are measures on a nominal scale i.e. where you use labels. For example, rocks can be generally categorized as igneous, sedimentary and metamorphic. The values that can be taken are called levels. Categorical variables have no numerical meaning but are often coded for easy of da ...
... Categorical variables are measures on a nominal scale i.e. where you use labels. For example, rocks can be generally categorized as igneous, sedimentary and metamorphic. The values that can be taken are called levels. Categorical variables have no numerical meaning but are often coded for easy of da ...
Agronomic Spatial Variability and Resolution
... Column letter of the lower right cell of an array of data Row number of the lower right cell of an array of data The “:” instructs Excel to include all data between the two corner cells ...
... Column letter of the lower right cell of an array of data Row number of the lower right cell of an array of data The “:” instructs Excel to include all data between the two corner cells ...
Chapter 13 - Faculty Website Listing
... similar to example above. (In each case, follow the suggested guidelines for class limits and class width.) ...
... similar to example above. (In each case, follow the suggested guidelines for class limits and class width.) ...
Sections 2.5 and 2.6 - University of South Carolina
... Interquartile range also easy to understand, gives length of middle 50% of data. SD uses all data but also prone to inflation by outliers. However, SD and mean are “classical” measures and form basis of computing confidence intervals, and hypothesis tests, so we’ll mainly use these from now on. ...
... Interquartile range also easy to understand, gives length of middle 50% of data. SD uses all data but also prone to inflation by outliers. However, SD and mean are “classical” measures and form basis of computing confidence intervals, and hypothesis tests, so we’ll mainly use these from now on. ...
Session Slides/Handout
... does not provide information about another unit’s value, given other factors (and the overall mean) in the analysis of the experiment, then the units are independent for this measurement. ...
... does not provide information about another unit’s value, given other factors (and the overall mean) in the analysis of the experiment, then the units are independent for this measurement. ...
Methods of Presenting Data - Penn Arts and Sciences
... number of individuals in each group, and X 1 and X 2 are the respective means. The calculated t value is then compared to the value in the table (Table 3) at the probability level chosen and at the combined degrees of freedom of the two samples (N1 + N2 2). If the value for t is less than that found ...
... number of individuals in each group, and X 1 and X 2 are the respective means. The calculated t value is then compared to the value in the table (Table 3) at the probability level chosen and at the combined degrees of freedom of the two samples (N1 + N2 2). If the value for t is less than that found ...
Summary - LearnEconometrics.com
... Required arguments are: the SAS dataset name variable name. Options include: AR=n DIF=(n) ...
... Required arguments are: the SAS dataset name variable name. Options include: AR=n DIF=(n) ...
Module 2
... mean(Tot Comp +…) = 4563 med(Tot Comp + …) = 1884 (both in $1000s) The median is a better measure because the mean gets pulled up by the upper extremes and is no longer a typical value. (If we asked, however, how much each CEO would get if the sum of all compensations were equally redistributed amon ...
... mean(Tot Comp +…) = 4563 med(Tot Comp + …) = 1884 (both in $1000s) The median is a better measure because the mean gets pulled up by the upper extremes and is no longer a typical value. (If we asked, however, how much each CEO would get if the sum of all compensations were equally redistributed amon ...
Methods for Describing Data I. Describing Qualitative Data (i
... The upper and lower quartiles of the data portrayed by the top and bottom of a rectangle, and the median is portrayed by a horizontal line segment within the rectangle. The mean is marked by a dot or a plus sign. The vertical lines (or “whiskers”) above and below the rectangle extend to the adjacent ...
... The upper and lower quartiles of the data portrayed by the top and bottom of a rectangle, and the median is portrayed by a horizontal line segment within the rectangle. The mean is marked by a dot or a plus sign. The vertical lines (or “whiskers”) above and below the rectangle extend to the adjacent ...
Final Exam Study Guide Spring 2003 FAMR 380
... B. median C. correlation D. any one of the above would be appropriate ...
... B. median C. correlation D. any one of the above would be appropriate ...
December 11, 2006
... Hint: Answer the question H0:μPRE = μPOST by using the test-scheme from the lecture (see below) 2. Calculate the 95%-confidence interval of the change in the countermeasure group. 3. Perform a suitable analysis to compare the changes in heart rate in the two groups. Hint: Answer the question H0:μ1=μ ...
... Hint: Answer the question H0:μPRE = μPOST by using the test-scheme from the lecture (see below) 2. Calculate the 95%-confidence interval of the change in the countermeasure group. 3. Perform a suitable analysis to compare the changes in heart rate in the two groups. Hint: Answer the question H0:μ1=μ ...
Agronomic Spatial Variability and Resolution
... better predictor of the expected or central value • Calculated by ranking the values from high to low – For an odd number of measurements, the median is middle value – For an even number of measurements, the median is average of the two middle ...
... better predictor of the expected or central value • Calculated by ranking the values from high to low – For an odd number of measurements, the median is middle value – For an even number of measurements, the median is average of the two middle ...