IBM SPSS Statistics Base 24
... the measurement level stored in the dictionary and is not affected by any temporary measurement level override specified by changing the measurement level in the source variable list on the Variables tab. This is not available for multiple response sets. Note: The measurement level for numeric varia ...
... the measurement level stored in the dictionary and is not affected by any temporary measurement level override specified by changing the measurement level in the source variable list on the Variables tab. This is not available for multiple response sets. Note: The measurement level for numeric varia ...
chapters. - Project MOSAIC
... very common to represent everything with a number. For C instance the categorical variable for sex, with levels male or female, might be stored as 0 or 1. Even categorical variables like race or language, with many different levels, can be represented as a number. The codebook provides the interpret ...
... very common to represent everything with a number. For C instance the categorical variable for sex, with levels male or female, might be stored as 0 or 1. Even categorical variables like race or language, with many different levels, can be represented as a number. The codebook provides the interpret ...
File - Essential Math
... All of Jennifer's scores seem to be fairly high. However, one judge only gave her a 3.0. This value is clearly not representative of Jennifer's abilities, as all the other judges gave her significantly higher scores. Therefore, in an Olympic competition, where scores can be extremely close, eliminat ...
... All of Jennifer's scores seem to be fairly high. However, one judge only gave her a 3.0. This value is clearly not representative of Jennifer's abilities, as all the other judges gave her significantly higher scores. Therefore, in an Olympic competition, where scores can be extremely close, eliminat ...
PASW® Statistics Base 18
... Technical Support services are available to maintenance customers. Customers may contact Technical Support for assistance in using PASW Statistics or for installation help for one of the supported hardware environments. To reach Technical Support, see the Web site at http://www.spss.com, or contact ...
... Technical Support services are available to maintenance customers. Customers may contact Technical Support for assistance in using PASW Statistics or for installation help for one of the supported hardware environments. To reach Technical Support, see the Web site at http://www.spss.com, or contact ...
IRCHART Statement
... The data set JETLIM contains one observation with the limits for process DIAM. The variables – LCLI– and – UCLI– contain the control limits for the individual measurements, and the variable – MEAN– contains the central line. The variables – LCLR– and – UCLR– contain the control limits for the moving ...
... The data set JETLIM contains one observation with the limits for process DIAM. The variables – LCLI– and – UCLI– contain the control limits for the individual measurements, and the variable – MEAN– contains the central line. The variables – LCLR– and – UCLR– contain the control limits for the moving ...
Moments and the Shape of Histograms
... measure that will overcome the fact that the median does not reflect the magnitudes of individual observations, only the number that is greater or smaller than the median. We need a measure that in some sense “balances” the smaller and the larger observations; we need to allow for a very large obser ...
... measure that will overcome the fact that the median does not reflect the magnitudes of individual observations, only the number that is greater or smaller than the median. We need a measure that in some sense “balances” the smaller and the larger observations; we need to allow for a very large obser ...
Chapter 2: Using Numerical Measures to Describe Data
... Measures of Relationships Between Variables Optional Material: Weighted Mean ...
... Measures of Relationships Between Variables Optional Material: Weighted Mean ...
IBM SPSS Statistics Base 22
... the measurement level stored in the dictionary and is not affected by any temporary measurement level override specified by changing the measurement level in the source variable list on the Variables tab. This is not available for multiple response sets. Note: The measurement level for numeric varia ...
... the measurement level stored in the dictionary and is not affected by any temporary measurement level override specified by changing the measurement level in the source variable list on the Variables tab. This is not available for multiple response sets. Note: The measurement level for numeric varia ...
DF SS n XX s = − − = 1
... applied in a similar fashion as in the Goodness-of-fit test. You may also use the Haber correction (Zar 4th edition pages 494-495; example 23.3). In Zar 5th edition, it is called the Cochran-Haber correction (pages 501-502, example 23.4). The Haber (Cochran-Haber) correction is actually simple, alth ...
... applied in a similar fashion as in the Goodness-of-fit test. You may also use the Haber correction (Zar 4th edition pages 494-495; example 23.3). In Zar 5th edition, it is called the Cochran-Haber correction (pages 501-502, example 23.4). The Haber (Cochran-Haber) correction is actually simple, alth ...
Quantitative Methods For Economic Analysis 1 - III Sem (2013 Admission)
... (ii) To simplify unwieldy and complex data : It is not easy to treat large numbers and hence they are simplified either by taking a few figures to serve as a representative sample or by taking average to give a bird’s eye view of the large masses. For example, complex data may be simplified by prese ...
... (ii) To simplify unwieldy and complex data : It is not easy to treat large numbers and hence they are simplified either by taking a few figures to serve as a representative sample or by taking average to give a bird’s eye view of the large masses. For example, complex data may be simplified by prese ...
Lesson 1 - Set theory and Set Operations
... if D = (Sales, Purchasing, Inventory, Payroll), then n[D] = 4. c) Set equality. Two sets are equal only if they have identical elements. Thus, if A = (x, y, z) and B = (x, y, z), then A = B. d) The Universal Set. In some problems in involving sets, it is necessary to consider one or more sets under ...
... if D = (Sales, Purchasing, Inventory, Payroll), then n[D] = 4. c) Set equality. Two sets are equal only if they have identical elements. Thus, if A = (x, y, z) and B = (x, y, z), then A = B. d) The Universal Set. In some problems in involving sets, it is necessary to consider one or more sets under ...
Technology Step-by-Step Using StatCrunch
... Technology Step-by-Step Using StatCrunch Section 1.3 Simple Random Sampling 1. Select Data, highlight Simulate Data, then highlight Discrete Uniform. 2. Fill in the following window with the appropriate values. To obtain a simple random sample for the situation in Example 2, we would enter the value ...
... Technology Step-by-Step Using StatCrunch Section 1.3 Simple Random Sampling 1. Select Data, highlight Simulate Data, then highlight Discrete Uniform. 2. Fill in the following window with the appropriate values. To obtain a simple random sample for the situation in Example 2, we would enter the value ...
Module 1 - ReStore
... individuals into „smoking‟ and „non-smoking‟ groups – that would not be ethnical (or possible!). However you could recruit individuals who are already smokers to your experimental group. You could control for factors like age, SEC, gender, marital status (anything you think might be important to you ...
... individuals into „smoking‟ and „non-smoking‟ groups – that would not be ethnical (or possible!). However you could recruit individuals who are already smokers to your experimental group. You could control for factors like age, SEC, gender, marital status (anything you think might be important to you ...
Getting Started with SPSS
... When you first open SPSS, the first screen you should see is the “What would you like to do?” window. This is asking for how you would like to enter the data. ...
... When you first open SPSS, the first screen you should see is the “What would you like to do?” window. This is asking for how you would like to enter the data. ...
Data Summarization Methods in Base SAS Procedures
... lowest value that occurs most often. To list all possible modes, use the MODES option in the PROC UNIVARIATE statement. Using PROC TABULATE The TABULATE procedure requires a PROC statement, either a CLASS statement or VAR statement, and a TABLE statement to display summary statistics in tabular form ...
... lowest value that occurs most often. To list all possible modes, use the MODES option in the PROC UNIVARIATE statement. Using PROC TABULATE The TABULATE procedure requires a PROC statement, either a CLASS statement or VAR statement, and a TABLE statement to display summary statistics in tabular form ...
Data Summarization Methods in Base SAS® Procedures
... lowest value that occurs most often. To list all possible modes, use the MODES option in the PROC UNIVARIATE statement. Using PROC TABULATE The TABULATE procedure requires a PROC statement, either a CLASS statement or VAR statement, and a TABLE statement to display summary statistics in tabular form ...
... lowest value that occurs most often. To list all possible modes, use the MODES option in the PROC UNIVARIATE statement. Using PROC TABULATE The TABULATE procedure requires a PROC statement, either a CLASS statement or VAR statement, and a TABLE statement to display summary statistics in tabular form ...
Analyzing Data: Looking for Patterns and
... The values on the left are the female percents, as in Figure 1.3, but ordered out from the stem, from right to left. The values on the right are the male percents. It is clear that literacy is generally higher among males than among females in these countries. Stemplots do not work well for large da ...
... The values on the left are the female percents, as in Figure 1.3, but ordered out from the stem, from right to left. The values on the right are the male percents. It is clear that literacy is generally higher among males than among females in these countries. Stemplots do not work well for large da ...
INTRODUCTION TO SPSS FOR WINDOWS
... 3. Edit the variable name under column labeled Name. The variable name must be eight characters or less in length. You can also specify the number of decimal places (under Decimals), assign a descriptive name (under Label), define missing values (under Missing), define the type of variable (under Me ...
... 3. Edit the variable name under column labeled Name. The variable name must be eight characters or less in length. You can also specify the number of decimal places (under Decimals), assign a descriptive name (under Label), define missing values (under Missing), define the type of variable (under Me ...
The Ultimate R Cheat Sheet – Data Management (Version 4
... row.names(dat1)=dat1$ID. assigns an ID field to row names. Note that the default row names are consecutive numbers. In order for this to work, each value in the ID field must be unique. To generate unique and descriptive row names that may serve as IDs, you can combine two or more variables: row.nam ...
... row.names(dat1)=dat1$ID. assigns an ID field to row names. Note that the default row names are consecutive numbers. In order for this to work, each value in the ID field must be unique. To generate unique and descriptive row names that may serve as IDs, you can combine two or more variables: row.nam ...
4. Statistics - Haese Mathematics
... Suppose we wish to find the views on extended shopping hours of shoppers at a huge supermarket. As people come and go, a simple random process is not practical. In such a situation systematic sampling may be used. To obtain a k% systematic sample the first member is chosen at random, ...
... Suppose we wish to find the views on extended shopping hours of shoppers at a huge supermarket. As people come and go, a simple random process is not practical. In such a situation systematic sampling may be used. To obtain a k% systematic sample the first member is chosen at random, ...
1 Exploring Data CASE STUDY
... 1.4 Virginia college tuitions Tuitions and fees for the 2005–2006 school year for 60 two- and fouryear colleges and universities in Virginia are shown in Table 1.2 (page 45) and the stemplot in Figure 1.4 (page 45) in Example 1.5. They ranged from a low of $2135 for the two-year community colleges t ...
... 1.4 Virginia college tuitions Tuitions and fees for the 2005–2006 school year for 60 two- and fouryear colleges and universities in Virginia are shown in Table 1.2 (page 45) and the stemplot in Figure 1.4 (page 45) in Example 1.5. They ranged from a low of $2135 for the two-year community colleges t ...
Lesson 3: Measures of Central Location and Dispersion
... Set A: 24, 25, 29, 29, 30, 31 mean = 28.0, median = 29 Set B: 24, 25, 29, 29, 30, 131 mean = 44.7, median = 29 Here difference in one observation alters the mean considerably, but does not change the median at all. Thus, the median is preferred over the mean as a measure of central location for data ...
... Set A: 24, 25, 29, 29, 30, 31 mean = 28.0, median = 29 Set B: 24, 25, 29, 29, 30, 131 mean = 44.7, median = 29 Here difference in one observation alters the mean considerably, but does not change the median at all. Thus, the median is preferred over the mean as a measure of central location for data ...
Kerns chapter on types of data and basic R
... This seems to be a simple problem, so it should have a simple solution. We should pick cells to facilitate our analysis. With continuous data the cells will have to be intervals. Of course, if we pick different cells, or different intervals, we are likely to get different results. But this is just a ...
... This seems to be a simple problem, so it should have a simple solution. We should pick cells to facilitate our analysis. With continuous data the cells will have to be intervals. Of course, if we pick different cells, or different intervals, we are likely to get different results. But this is just a ...
SPSS Advanced Statistics 17.0
... multiple comparison tests are performed for each dependent variable separately. Residuals, predicted values, Cook’s distance, and leverage values can be saved as new variables in your data file for checking assumptions. Also available are a residual SSCP matrix, which is a square matrix of sums of s ...
... multiple comparison tests are performed for each dependent variable separately. Residuals, predicted values, Cook’s distance, and leverage values can be saved as new variables in your data file for checking assumptions. Also available are a residual SSCP matrix, which is a square matrix of sums of s ...
XSCHART Statement
... The data set TURBLIM contains one observation with the limits for process KWATTS. The variables – LCLX– and – UCLX– contain the lower and upper control chart, and the variables – LCLS– and – UCLS– contain the lower and limits for the X upper control limits for the s chart. The variable – MEAN– con ...
... The data set TURBLIM contains one observation with the limits for process KWATTS. The variables – LCLX– and – UCLX– contain the lower and upper control chart, and the variables – LCLS– and – UCLS– contain the lower and limits for the X upper control limits for the s chart. The variable – MEAN– con ...