Index

A

  1. A priori probability: definition of;
    1. overview of
  2. Absolute cell references
  3. Absolute differences
  4. Addition rule: mutual exclusivity and;
    1. overview of
  5. Adjusted R2: definition of;
    1. overview of
  6. Admission data: calculating age using =YEARFRAC ( ) function;
    1. DOA;
    2. DOB
  7. Age at admission
  8. Aldrich, J.
  9. Alpha: beta's mutual dependence with;
    1. cost and;
    2. definition of; F probability;
    3. inflation;
    4. intervention and;
    5. research and; as small;
    6. specifying
  10. Alternative hypothesis: beta for;
    1. selecting; t value and
  11. Analysis of variance (ANOVA);
    1. Data Analysis package instructions; definition of;
    2. differences;
    3. Excel add-in for;
    4. F test for differences in;
    5. within health care industry;
    6. Lean/Six Sigma practices and;
    7. output; overview of;
    8. for repeated measures;
    9. t test relation;
    10. as test;
    11. variation within.
    12. See also One-way analysis of variance
  12. Analysis ToolPak. See Data Analysis pack
  13. =AND ( ) function
  14. ANOVA. See Analysis of variance
  15. Appel, F. A.
  16. Area, normal curve approximation
  17. Arguments: definition of;
    1. functions and;
    2. number of
  18. Arrays: definition of;
    1. determinant of;
    2. functions
  19. Automatic curve fitter
  20. Average. See Mean
  21. =AVERAGE ( ) function
  22. =AVERAGE ( ) function

B

  1. b coefficients
  2. b0
  3. Backward stepwise elimination
  4. Bar chart
  5. Bartlett test
  6. Bayes's theorem: conditional probability and;
    1. overview of
  7. Bell-shaped curve
  8. Bernoulli distribution: definition of;
    1. random numbers from
  9. Best regression model: Dust Bowl empiricism;
    1. overview of;
    2. with regression variables;
    3. theory. See also Stepwise regression
  10. Best-fitting line
  11. Betas: alpha's mutual dependence with;
    1. for alternative hypothesis;
    2. calculating;
    3. controlling;
    4. cost and;
    5. definition of; determining;
    6. for hypothesis;
    7. intervention and;
    8. as many;
    9. one-tail test and;
    10. reality of; research and;
    11. as small;
    12. specifying; value of
  12. Between group variance (SSB)
  13. Binary logic: coin flip application of;
    1. emergency visit application of;
    2. nonemergency visit application of
  14. =BINOMDIST ( ) function
  15. Binomial distributions; definition of;
    1. equations for;
    2. health care professional applications;
    3. Medicare;
    4. random numbers from
  16. Binomial probabilities: =BINOMDIST ( ) function;
    1. Medicare;
    2. overview of
  17. Bins: defining;
    1. for frequency distribution
  18. Breast cancer education
  19. Brook, R. H.

C

  1. Calculus: behind formulas;
    1. solution provided by
  2. Carteret Falls regional hospital
  3. Case: cost per;
    1. deletion
  4. Categorical data: confidence limits and;
    1. descriptive statistics and;
    2. statistical tests for
  5. Categorical variables: definition of;
    1. frequencies of;
    2. numerical variable transformation of;
    3. overview of;
    4. pivot table and
  6. Causal variable
  7. Causality
  8. Caused variable
  9. Cell references, dollar sign convention for
  10. Cells: copying;
    1. expected values in;
    2. functions and;
    3. highlighting.
  11. See also Contiguous cells; Noncontiguous cells; Range
  12. Centers for Medicare and Medicaid Services (CMS)
  13. Central tendency: definition of;
    1. functions for; mean;
    2. median; mode.
    3. See also Measures of central tendency and dispersion
  14. Changes, undoing
  15. Chart function, frequency distribution graphed by
  16. Charts: audit;
    1. bar;
    2. data;
    3. definition of;
    4. function;
    5. line;
    6. modifying;
    7. overview of;
    8. Pareto; pie;
    9. types;
    10. XY(Scatter)
  17. =CHIDIST ( ) function
  18. =CHIINV ( ) function
  19. Chi-square: Type I errors and;
    1. Type II errors and
  20. Chi-square analyses: dichotomous categorical variable;
    1. examples of;
    2. issues with
  21. Chi-square critical value
  22. Chi-square statistic;
    1. definition of;
    2. df;
    3. interpreting;
    4. n-by-n tables;
    5. n-by-two table;
    6. small expected values in;
    7. two-by-n table
  23. Chi-square test: Logit;
    1. overview of;
    2. statistical independence and
  24. =CHITEST ( ) function
  25. Cluster samples: definition of;
    1. overview of;
    2. stratified samples versus
  26. CMS. See Centers for Medicare and Medicaid Services
  27. Coefficient of determination (R2): calculating;
    1. definition of;
    2. overview of;
    3. pseudo; statistic
  28. Coefficients: of b;
    1. correlation;
    2. Logit;
    3. solving for
  29. Coin flips, binary logic applied to
  30. Color code
  31. Column chart
  32. Columns
  33. Combinatorial formulas
  34. Conditional probabilities: Bayes's theorem and;
    1. data frequencies and;
    2. definition of;
    3. independence tested by;
    4. independent events and;
    5. marginal probabilities and;
    6. mathematical independence link;
    7. overview of;
    8. tables
  35. Confidence intervals: definition of;
    1. overview of;
    2. point estimates and
  36. Confidence levels: sample size and; t values
  37. Confidence limits: =AND ( ) function;
    1. calculating;
    2. categorical data and;
    3. confidence level t values;
    4. descriptive statistics and;
    5. hypothesis testing and;
    6. for multiple samples; 95 percent;
    7. one-tail t values;
    8. two-tail t values
  38. Constant
  39. Constant variance assumption
  40. Contiguous cells
  41. Contingency table
  42. Continuous numerical variables: definition of;
    1. overview of
  43. Continuous probability distributions: normal distribution;
    1. overview of
  44. Control group
  45. Copying
  46. Correlation: coefficient;
    1. definition of;
    2. multicollinearity and
  47. Cost: alpha and;
    1. beta and;
    2. of intervention;
    3. per case;
    4. of research
  48. =COUNT ( ) function
  49. =COUNTIF ( ) function
  50. Critical value: chi-square;
    1. definition of
  51. Cross-tabulation. See also Contingency table
  52. Cumulative differences
  53. Cumulative frequencies: creating;
    1. definition of;
  54. percentage distributions and
  55. Cumulative normal distributions: area;
    1. overview of
  56. Cumulative percentage distribution

D

  1. Data: categorical;
    1. chart;
    2. delimited;
    3. display;
    4. drag and drop;
    5. formatting;
    6. identifying;
    7. imported;
    8. inspecting; line fit to;
    9. modifying;
    10. moving;
    11. nature of;
    12. overview of;
    13. as related;
    14. as secondary;
    15. sorting;
    16. as unrelated
  2. Data access: data preparation and;
    1. overview of
  3. Data acquisition. See Data preparation;
    1. Sampling
  4. Data Analysis add-in: multiple regression using;
    1. output;
    2. samples drawn with;
    3. t test.
    4. See also Random Number Generation dialog box
  5. Data Analysis package;
    1. ANOVA instructions;
    2. definition of;
    3. linear regression instructions
  6. Data checks, performing
  7. Data frequencies, conditional probabilities and
  8. Data preparation: data access and;
    1. sampling and.
    2. See also Secondary data
  9. Data ranges: definition of;
    1. overview of
  10. Date of admission (DOA)
  11. Date of birth (DOB)
  12. Dates
  13. Decisions
  14. Degrees of freedom (df);
    1. chi-square statistic;
    2. definition of;
    3. overview of;
    4. small expected values and
  15. Delimited data.
    1. See also Fixed-length
  16. Dependent variables;
    1. analysis;
    2. chi-square analysis;
    3. comparison;
    4. definition of;
    5. estimates of;
    6. example with;
    7. independent variables and;
    8. introduction to;
    9. issues;
    10. Logit;
    11. multiple regression and;
    12. OLS;
    13. overview of;
    14. problems;
    15. traditional treatments;
    16. WLS.
    17. See also Dichotomous dependent variable; Linear regression
  17. Descriptive presentation
  18. Descriptive statistics: categorical data and;
    1. confidence limits and
  19. Determinant: definition of;
    1. finding
  20. df. See Degrees of freedom
  21. Diagnostic-related group (DRG)
  22. Dialog boxes: Function Arguments;
    1. Insert Chart;
    2. Insert Function;
    3. Paste Special;
    4. Random Number Generation;
    5. Select Data Source
  23. Dichotomous dependent variables: analysis with;
    1. chi-square analysis;
    2. example with;
    3. introduction to;
    4. issues;
    5. Logit for estimating;
    6. OLS with;
    7. overview of;
    8. problems;
    9. traditional treatments
  24. Differences;
    1. absolute;
    2. ANOVA;
    3. cumulative;
    4. regression establishing;
    5. significant;
    6. statistical tests establishing
  25. Direct input
  26. Discrete distribution: definition of;
    1. parameters requested by;
    2. random numbers from
  27. Discrete numerical variables;
    1. definition of;
    2. mean of;
    3. standard deviation of
  28. Dispersion: definition of; overview of.
    1. See also Measures of central tendency and dispersion
  29. Distribution, of proportion
  30. #DIV/0!
  31. DOA. See Date of admission
  32. DOB. See Date of birth
  33. Documentation
  34. $ convention
  35. Double-blind random clinical trial
  36. Drag and drop
  37. DRG. See Diagnostic-related group
  38. Dummy variables;
    1. definition of;
    2. formulas;
    3. with interaction;
    4. in multiple regression;
    5. nonlinear relationships and;
    6. as predictor variable;
    7. terms.
    8. See also Dichotomous dependent variables
  39. Dust Bowl empiricism

E

  1. ED. See Emergency department
  2. Effect, residual variation versus
  3. Emergency department (ED)
  4. Emergency room, Poisson distribution application
  5. Emergency visits, binary logic applied to
  6. Empirical probabilities: definition of;
    1. frequency of occurrence and;
    2. independence and;
    3. overview of;
    4. probability distributions and;
    5. sequential events and
  7. Empiricism, Dust Bowl
  8. Equal variances: assumption of;
    1. F test;
    2. t tests and;
    3. testing for
  9. Equations: for binomial distribution;
    1. of line;
    2. for one-way analysis of variance;
    3. for Poisson distribution;
    4. regression;
    5. simultaneous;
    6. solving;
    7. for TC
  10. Error variance
  11. Estimated variance, standard error with
  12. Estimates: comparison of;
    1. of dependent variable
  13. Events: definition of;
    1. as independent;
    2. outcomes and;
    3. sample space and
  14. Excel Charts function. See Charts
  15. Excel functions. See Functions
  16. Excel graphs. See Graphs
  17. =EXP ( ) function
  18. Expected values: in cells;
    1. as small
  19. Explained variance: understanding;
    1. unexplained variance versus
  20. Exponential model

F

  1. F probability, alpha inflation protection
  2. F statistic: definition of;
    1. overview of; WLS
  3. F tests: for ANOVA differences;
    1. calculating;
    2. definition of;
    3. equal variance;
    4. =FDIST ( ) function;
    5. =FINV ( ) function; interpreting;
    6. null hypothesis and;
    7. overview of;
    8. t test versus
  4. =FACT ( ) function
  5. Factorial analysis of variance (Factorial ANOVA)
  6. Factorial design: definition of;
    1. repeated measures in
  7. Factorials
  8. =FDIST ( ) function
  9. F4 function key
  10. Finite population correction (fpc): definition of; overview of
  11. =FINV ( ) function
  12. Fisher exact test
  13. Fixed-length. See also Delimited data
  14. Form CMS-485
  15. Format Trendline option
  16. Formulas; bar;
    1. calculus behind;
    2. combinatorial;
    3. dummy variable;
    4. line;
    5. for multiple regression;
    6. for SST
  17. Forward stepwise inclusion
  18. fpc. See Finite population correction
  19. Frequency distributions: Bernoulli;
    1. binomial;
    2. Bins for;
    3. of categorical variables;
    4. chart function graphing;
    5. creating;
    6. cumulative;
    7. cumulative normal;
    8. cumulative percentage;
    9. discrete;
    10. displaying;
    11. =FREQUENCY ( ) function creating;
    12. graphs of;
    13. mean creating;
    14. normal;
    15. overview of;
    16. percentage;
    17. pivot table generating;
    18. Poisson;
    19. sampling;
    20. skewed;
    21. standard deviation creating;
    22. types of;
    23. understanding;
    24. uniform
  20. =FREQUENCY ( ) function;
    1. definition of;
    2. structure of; use of
  21. Frequency of occurrence, empirical probability and
  22. Function Arguments dialog box
  23. Functions;
    1. =AND ( );
    2. arguments and;
    3. array;
    4. =AVERAGE ( );
    5. =BINOMDIST ( );
    6. cells and;
    7. for central tendency;
    8. chart;
    9. =CHIDIST ( );
    10. =CHIINV ( ); =CHITEST ( );
    11. =COUNT ( );
    12. =COUNTIF ( );
    13. definition of;
    14. direct input of;
    15. =EXP ( );
    16. =FACT ( );
    17. =FDIST ( );
    18. =FINV ( );
    19. =FREQUENCY ( );
    20. =IF ( );
    21. =MAX ( );
    22. =MDETERM;
    23. =MEDIAN ( );
    24. =MIN ( );
    25. =MINVERSE;
    26. =MMULT ( );
    27. =MODE ( ); as nested;
    28. Nested =IF ( );
    29. =NORMDIST ( );
    30. =OR ( );
    31. overview of;
    32. =POISSON ( );
    33. =POISSON ( );
    34. =RAND ( );
    35. =RANDBETWEEN ( );
    36. =ROUND ( );
    37. =SQRT ( );
    38. =STDEV ( );
    39. =SUM ( );
    40. =SUMPRODUCT ( );
    41. =SUMSQ ( );
    42. =TDIST ( );
    43. =TINV;
    44. =TRANSPOSE ( );
    45. =TRUNC ( );
    46. =TTEST ( );
    47. =VAR ( );
    48. =VARP ( );
    49. =YEARFRAC ( )

G

  1. Gender, LOS and
  2. Goldberger, A. S.
  3. Graphing capability
  4. Graphs: formatting;
    1. of frequency distribution;
    2. overview of
  5. Groups: means;
    1. sampling;
    2. selecting;
    3. t tests for comparing two;
    4. =TDIST function

H

  1. Halpern, C. T.
  2. Harmon, H. H.
  3. HDI. See Human Development Index
  4. Header row
  5. Health administration
  6. Health care industry: ANOVA within;
    1. Lean/Six Sigma practices within
  7. Health care personnel: binomial applications to;
    1. standard hourly rates for
  8. Health policy
  9. Highlighting
  10. Histogram
  11. Home health agency
  12. Homogeneity of variance
  13. Hospital: admissions;
    1. alliance;
    2. factorial example
  14. Human Development Index (HDI)
  15. Hypotheses: acceptance of; beta for;
    1. definition of;
    2. of independence testing;
    3. initial; rejection of;
    4. statements;
    5. t tests and;
    6. t value and.
    7. See also Alternative hypothesis; Null hypothesis
  16. Hypothesis testing: confidence limits and;
    1. definition of;
    2. overview of;
    3. population; sample;
    4. sample size and.
    5. See also Type I errors; Type II errors

I

  1. ICD-9. See International Classification of Diseases, ninth revision
  2. Identity matrix
  3. =IF ( ) function: definition of;
    1. as nested;
    2. overview of
  4. =IF ( ) statement: date of birth checked by;
    1. M or F, checked by
  5. Imported data
  6. Imputation
  7. Independence: conditional probability tables testing;
    1. definition of;
    2. empirical probabilities and.
    3. See also Hypothesis of independence; Mathematical independence; Statistical independence
  8. Independent events: conditional probability and;
    1. overview of
  9. Independent variables;
    1. analyzing;
    2. definition of;
    3. dependent variables and;
    4. multiple regression and;
    5. regression coefficients for.
    6. See also Causal variable; Linear regression; Predictor variable
  10. Inferential statistics
  11. Information matrix: calculation of;
    1. definition of;
    2. =MMULT ( ) function;
    3. overview of;
    4. =TRANSPOSE ( ) function
  12. Insert Chart dialog box
  13. Insert Function dialog box
  14. Interaction, dummy variables with
  15. Interaction effect.
    1. See also Main effect
  16. Interaction terms: comments on;
    1. as predictor
  17. Intercept
  18. Internal frequencies
  19. International Classification of Diseases, ninth revision (ICD-9).
    1. See also Secondary data
  20. Interval scale
  21. Interval variables: definition of;
    1. overview of
  22. Intervention: alpha and;
    1. beta and;
    2. cost of;
    3. research and
  23. Inverse

J

  1. Joint probabilities: building;
    1. definition of;
    2. “or” values;
    3. overview of

K

  1. Known variance, standard error with
  2. Kros, J. F.

L

  1. Lean/Six Sigma practices: ANOVA and;
    1. within health care industry
  2. Length of stay (LOS);
    1. calculating;
    2. gender and
  3. Levine, D. M.
  4. Likert scale
  5. Line: data fitting of;
    1. equations of.
    2. See also Best-fitting straight line
  6. Line chart
  7. Linear probability model (LPM);
    1. definition of;
    2. problem;
    3. WLS for estimating.
    4. See also Weighted least squares
  8. Linear regression;
    1. best-fitting straight line;
    2. calculation of;
    3. Data Analysis package instructions;
    4. definition of;
    5. meaning of.
    6. See also Simple linear regression
  9. Linear relationships: determining;
    1. log;
    2. straight line
  10. Log linear relationships
  11. Logarithmic model
  12. Logistic regression
  13. Logit;
    1. chi-square test;
    2. coefficients;
    3. definition of;
    4. dependent variable;
    5. for dichotomous dependent variable estimation;
    6. equation of;
    7. introduction to;
    8. models;
    9. OLS compared with;
    10. overview of;
    11. pseudo R square statistic;
    12. setting up;
    13. significance test with;
    14. Solver for;
    15. standard errors;
    16. WLS and
  14. Log-likelihoods: coefficients;
    1. finding;
    2. maximizing;
    3. Solver used for;
    4. spreadsheet layout for
  15. LOS. See Length of stay
  16. LPM. See Linear probability model

M

  1. M or F
  2. Maddala, G. S.
  3. Main effect.
    1. See also Interaction effect
  4. Marginal frequencies
  5. Marginal probabilities: conditional probabilities and;
    1. definition of;
    2. mathematical independence link;
    3. overview of
  6. Mathematical independence;
    1. conditional probabilities link;
    2. marginal probabilities link;
    3. overview of
  7. Mathematical operations
  8. Matrices: addition of;
    1. definition of;
    2. determinant of;
    3. Excel and;
    4. identity;
    5. introduction to;
    6. manipulating;
    7. multiple regression and;
    8. multiplication of;
    9. overview of;
    10. scalars and;
    11. subtraction of.
    12. See also Arrays; Information matrix
  9. Matrix math functions
  10. =MAX ( ) functions: definition of;
    1. =MIN ( ) function and; overview of
  11. Maximum likelihood: definition of;
    1. estimators; process
  12. McDermott, Richard
  13. =MDETERM function
  14. Means: center;
    1. definition of;
    2. of discrete numerical variable;
    3. frequency distribution created with;
    4. group;
    5. measures of dispersion and;
    6. overview of;
    7. representative sample inferring;
    8. of samples;
    9. sampling distribution of;
    10. standard error of;
    11. t test comparing
  15. Measurement error, sample size and
  16. Measures of central tendency and dispersion: calculating;
    1. as complicated; mean center and;
    2. overview of
  17. Median: definition of;
    1. overview of
  18. =MEDIAN ( ) function
  19. Medicare.
    1. See also Secondary data
  20. Microsoft Excel: array functions;
    1. automatic curve fitter;
    2. basics;
    3. Exponential model in;
    4. Format Trendline option;
    5. matrix and;
    6. Moving Average model in;
    7. output;
    8. overview of;
    9. Polynomial option in;
    10. Power option in;
    11. scientific notation;
    12. as statistical tool;
    13. stepwise regression in;
    14. terms;
    15. trendline options;
    16. WLS in
  21. Microsoft Excel add-in: for ANOVA;
    1. for factorial ANOVA;
    2. for one-way analysis of variance;
    3. regression;
    4. for related data;
    5. for repeated measures
  22. =MIN ( ) functions: definition of;
    1. =MAX ( ) function and;
    2. overview of
  23. =MINVERSE function
  24. Missing data: case deletion;
    1. imputation;
    2. missing;
    3. overview of;
    4. remedies
  25. =MMULT ( ) function;
    1. definition of;
    2. information matrix;
    3. overview of; using
  26. Mode: definition of;
    1. overview of
  27. =MODE ( ) function
  28. Models: best regression;
    1. comparison of;
    2. exponential;
    3. in graphical form;
    4. linear probability;
    5. logarithmic;
    6. Logit;
    7. polynomial; power;
    8. prediction of; survival
  29. Monte Carlo technique
  30. Moving Average model
  31. Multicollinearity: correlation and;
    1. definition of;
    2. overview of
  32. Multiple R: definition of;
    1. overview of
  33. Multiple regression: calculation;
    1. concepts;
    2. Data Analysis add-in;
    3. definition of;
    4. dependent variable and;
    5. dummy variables in;
    6. extensions of;
    7. formula for;
    8. independent variable and;
    9. matrices and;
    10. output;
    11. overview of;
    12. problem;
    13. purpose of;
    14. results;
    15. solution
  34. Mutual exclusivity: addition rule and;
    1. simple addition rule and
  35. Mutually exclusive outcomes

N

  1. n - 1, sample variance and
  2. #NAME?
  3. n-by-n tables: chi-square statistic;
    1. example of
  4. n-by-two table: chi-square statistic;
    1. example of
  5. Nelson, F.
  6. Nested functions
  7. Nested =IF ( ) functions: decisions made by;
    1. overview of
  8. Newborns
  9. 95 percent; confidence limit;
    1. overview of
  10. 99 percent
  11. Nominal variable
  12. Noncontiguous cells
  13. Nonemergency visits, binary logic applied to
  14. Nonlinear relationships: definition of;
    1. dummy variables and;
    2. estimating;
    3. fitting;
    4. introduction to;
    5. log linear relationships;
    6. overview of;
    7. second-degree curves and
  15. Nonrandom samples
  16. Normal curve, area approximated under
  17. Normal distributions;
    1. calculations for;
    2. characteristics of;
    3. constructing;
    4. continuous probability distributions;
    5. definition of;
    6. introduction to;
    7. 95 percent in;
    8. 99 percent in;
    9. overview of;
    10. random numbers from;
    11. 68 percent in;
    12. standard deviation and;
    13. t distribution approximating.
    14. See also Cumulative normal distributions
  18. =NORMDIST ( ) function
  19. Null hypothesis: accepting;
    1. F tests and;
    2. rejecting;
    3. testing
  20. #NUM!
  21. Numerical variables: categorical variables transforming into;
    1. definition of;
    2. overview of.
    3. See also Continuous numerical variables; Discrete numerical variables

O

  1. Observations: percentage of;
    1. t distribution and
  2. OLS. See Ordinary least squares
  3. One-tail t values
  4. One-tail tests: betas and;
    1. overview of;
    2. two-tail t tests and
  5. One-way analysis of variance: calculation of;
    1. equations for;
    2. Excel add-in for;
    3. overview of
  6. =OR ( ) function
  7. =OR ( ) statement, M or F checked by
  8. “Or” values
  9. Ordinal scale
  10. Ordinal variables: definition of; overview of
  11. Ordinary least squares (OLS);
    1. definition of;
    2. dependent variable;
    3. with dichotomous dependent variable;
    4. Logit compared with;
    5. problems with;
    6. WLS compared with
  12. Outcomes: definition of;
    1. events and;
    2. as mutually exclusive;
    3. overview of;
    4. sample space and
  13. Output

P

  1. Parameters;
    1. definition of;
    2. discrete distribution requesting
  2. Pareto chart: definition of;
    1. overview of
  3. Paste Special dialog box
  4. Patterned distribution
  5. Pentad Home Health Agency
  6. Percentage distributions: creating;
    1. cumulative frequencies and
  7. Pie chart
  8. Pivot table: categorical variables and;
    1. frequencies generated by;
    2. with two variables
  9. Point estimates, confidence intervals and
  10. Poisson distribution: calculating;
    1. definition of;
    2. emergency room application;
    3. equations for;
    4. overview of;
    5. random numbers from
  11. =POISSON ( ) function
  12. =POISSON ( ) function
  13. Polynomial model
  14. Polynomial option
  15. Pooled variance: t test;
    1. for unequal sample sizes
  16. Population size: sample size and;
    1. standard error and
  17. Populations: definition of;
    1. hypothesis testing;
    2. proportions;
    3. random sample drawn from;
    4. samples and;
    5. target.
    6. See also Sampled population
  18. Power model
  19. Power option
  20. Predicted values of total charges (TC)
  21. Prediction, of model
  22. Predictor, interaction terms as
  23. Predictor variable
  24. Probabilities;
    1. basic concepts of;
    2. binomial;
    3. conditional;
    4. definitions;
    5. empirical;
    6. joint;
    7. marginal;
    8. a priori;
    9. stochastic process and;
    10. of t value. See also Coin flips;
    11. Normal distributions;
    12. Poisson distribution;
    13. Statistics;
    14. specific probabilities
  25. Probability distributions, empirical probability and
  26. Probability terminology/concepts: coin flips;
    1. empirical probability;
    2. events;
    3. independent events;
    4. mutually exclusive outcomes;
    5. sample space
  27. Probit
  28. Proportions: distribution of;
    1. population
  29. pseudo R square statistic
  30. Pseudorandom number

Q

  1. Quick Access Toolbar

R

  1. R square statistic
  2. R2. See Coefficient of determination
  3. =RAND ( ) function;
    1. copying;
    2. definition of;
    3. overview of;
    4. random number generation with;
    5. random number regeneration;
    6. using;
    7. working with
  4. =RANDBETWEEN ( ) function
  5. Random number generation: with =RAND ( ) function;
    1. sample drawing and
  6. Random Number Generation dialog box
  7. Random numbers: from Bernoulli distribution;
    1. from binomial distribution;
    2. from discrete distribution;
    3. from normal distribution;
    4. from Poisson distribution;
    5. =RAND ( ) function;
    6. regeneration;
    7. tables;
    8. from uniform distribution
  8. Random samples;
    1. definition of;
    2. of home health agency records;
    3. population drawing of.
    4. See also Simple random samples
  9. Random seed
  10. Range;
    1. definition of;
    2. overview of
  11. Ratio: scale;
    1. variables
  12. Regression;
    1. analyzing;
    2. b coefficients used for;
    3. best model of;
    4. difference established by;
    5. equations;
    6. Excel add-in;
    7. linear;
    8. logistic;
    9. meaning of;
    10. output;
    11. overview of;
    12. in practical terms;
    13. results;
    14. solving;
    15. stepwise;
    16. t test's relationship with;
    17. variables related by;
    18. variance. See also Nonlinear relationships;
    19. specific regression
  13. Regression coefficients: calculating;
    1. definition of;
    2. for independent variables
  14. Regression package, WLS and
  15. Regression variables, best regression model with
  16. Related data: Excel add-in for;
    1. t tests for
  17. Relationships, identifying
  18. Relative cell references
  19. Repeated measures: ANOVA for;
    1. definition of;
    2. Excel add-in for;
    3. in factorial design
  20. Replacement, sampling with
  21. Representative sample, mean inferred by
  22. Research: alpha and;
    1. beta and;
    2. cost of;
    3. intervention and
  23. Residual variation, effect versus
  24. =ROUND ( ) function

S

  1. Sample mean, integrating
  2. Sample sizes: confidence level and;
    1. determining;
    2. hypothesis testing and;
    3. as large;
    4. measurement error and;
    5. population size and;
    6. selecting;
    7. standard error influenced by.
    8. See also Unequal sample sizes
  3. Sample space: definition of;
    1. events and;
    2. outcomes and;
    3. overview of
  4. Sample variance, n - 1 and
  5. Sampled population: definition of;
    1. overview of
  6. Samples: =AND ( ) function;
    1. big picture and;
    2. cluster;
    3. comparing;
    4. confidence limits for multiple;
    5. Data Analysis add-in drawing;
    6. definition of;
    7. hypothesis testing;
    8. means of;
    9. nonrandom;
    10. populations and;
    11. random;
    12. random number generation and;
    13. simple random;
    14. stratified;
    15. systematic.
    16. See also specific samples
  7. Sampling;
    1. data preparation and;
    2. groups;
    3. overview of;
    4. with replacement;
    5. as stratified;
    6. t test
  8. Sampling distribution of mean: overview of;
    1. standard error
  9. Scalars: definition of;
    1. matrix multiplication and
  10. Scale, variables as
  11. Scatterplots: definition of;
    1. examining;
    2. importance of;
    3. visual inspection of
  12. Scientific notation
  13. Sea Coast Alliance
  14. Secondary data: definition of;
    1. examination of;
    2. overview of
  15. Second-degree curves, nonlinear relationships and
  16. Select Data Source dialog box
  17. Sequential events, empirical probabilities and
  18. Significance test, with Logit
  19. Significant difference
  20. Simple addition rule, mutual exclusivity and
  21. Simple average. See Mean
  22. Simple linear regression, extension of
  23. Simple multiplication rule
  24. Simple random samples: definition of;
    1. overview of
  25. Simultaneous equations
  26. Single-variable regression
  27. 68 percent
  28. Skewed distributions: definition of;
    1. overview of
  29. Skewed left
  30. Skewed right
  31. Slope intercept form
  32. Small alpha
  33. Small beta
  34. Small expected values
  35. Solver: definition of;
    1. limitations to;
    2. for Logit problem;
    3. overview of;
    4. setting up
  36. Sort routine
  37. Sorting data
  38. Spreadsheet Modeling for Business Decisions (Kros)
  39. Spreadsheets: definition of;
    1. log-likelihood layout;
    2. moving around in;
    3. as workbooks;
    4. working in
  40. =SQRT ( ) function
  41. Square root method
  42. SSB. See Between group variance
  43. SScols. See Sum of squares between columns
  44. SSrows. See Sum of squares between rows
  45. SSrows. cols. See Sum of squares due to interaction
  46. SST. See Total sums of squares; Total variance
  47. SSW. See Within group variance
  48. SSWC. See Sum of squares within cells
  49. Standard deviations: calculating;
    1. definition of;
    2. of discrete numerical variable;
    3. frequency distribution created by;
    4. normal distribution and;
    5. overview of
  50. Standard error of estimates: definition of;
    1. overview of
  51. Standard errors;
    1. calculating;
    2. concept of;
    3. definition of;
    4. with estimated variance;
    5. inflation;
    6. integrating;
    7. with known variance;
    8. Logit;
    9. of means;
    10. overview of;
    11. population size and;
    12. sample size influencing;
    13. sampling distribution of mean
  52. Standard hourly rates
  53. The State of the World's Children 1996 (UNICEF)
  54. The State of the World's Children 2001 (UNICEF)
  55. Statistical independence;
    1. chi-square test and;
    2. overview of
  56. Statistical significance
  57. Statistical tests: for categorical data;
    1. difference established by;
    2. overview of.
    3. Chi-square test;
    4. Regression;
    5. t tests
    6. See also Analysis of variance;
  58. Statistical tools, Excel as
  59. Statistics: caveats;
    1. chi-square;
    2. definition of;
    3. descriptive;
    4. F;
    5. inferential;
    6. pseudo;
    7. R2;
    8. variable applications of.
    9. See also specific statistics, Statistics for Managers Using Microsoft Excel (Levine, Stephan, and Szabat)
  60. =STDEV ( ) function
  61. Stephan, D.
  62. Stepwise regression: backward stepwise elimination;
    1. definition of;
    2. in Excel;
    3. forward stepwise inclusion;
    4. overview of
  63. Stochastic process: definition of;
    1. overview of
  64. Stratified samples: cluster samples versus
    1. definition of;
    2. overview of
  65. Studies in Family Planning
  66. Successive elimination
  67. Sudan
  68. =SUM ( ) function
  69. Sum of squares between columns (SScols): calculation of;
    1. variation
  70. Sum of squares between rows (SSrows): calculation of;
    1. variation
  71. Sum of squares due to interaction (SSrows . cols): calculation of;
    1. variation
  72. Sum of squares within cells (SSWC): calculation of;
    1. variation
  73. Summations
  74. =SUMPRODUCT ( ) function
  75. Sums of squares
  76. =SUMSQ ( ) function
  77. Survival analysis
  78. Syntax
  79. Systematic samples;
    1. definition of;
    2. overview of
  80. Szabat, K. A.

T

  1. t distribution: definition of;
    1. normal distribution approximated by;
    2. observations percentage and;
    3. overview of;
    4. shape of
  2. t statistic
  3. t tests;
    1. ANOVA relation;
    2. calculating;
    3. calculation of;
    4. Data Analysis add-in;
    5. definition of;
    6. equal variance and;
    7. F test versus;
    8. for group comparison;
    9. hypotheses and;
    10. interpreting;
    11. means compared with;
    12. origin of;
    13. overview of;
    14. pooled variance;
    15. regression's relationship with;
    16. for related data;
    17. results;
    18. sampling;
    19. selection in;
    20. =TDIST function;
    21. Type I error link;
    22. Type II error link;
    23. for unequal sample sizes;
    24. for unrelated data.
    25. See also One-tail test;Two-tail t tests
  4. t values: alternative hypothesis and;
    1. confidence level;
    2. finding;
    3. hypothesis and;
    4. one-tail;
    5. probability of;
    6. two-tail
  5. Target population
  6. TC. See Predicted values of total charges
  7. =TDIST ( ) function
  8. Telephones
  9. Text Import Wizard
  10. =TINV function
  11. Total sums of squares (SST): calculation of;
    1. variation
  12. Total variance (SST);
    1. calculation of;
    2. computation of;
    3. dividing;
    4. formula for
  13. Traditional treatments
  14. Transpose
  15. =TRANSPOSE ( ) function
  16. Trend line
  17. Trendline options
  18. =TRUNC ( ) function
  19. =TTEST ( ) function
  20. Two variables. See Independence
  21. Two-by-n table: chi-square statistic;
    1. example of
  22. Two-tail t tests: one-tail tests and;
    1. overview of
  23. Two-tail t values
  24. Type I errors: avoiding;
    1. chi-square and;
    2. definition of;
    3. overview of;
    4. t test link;
    5. Type II errors and
  25. Type II errors: avoiding;
    1. chi-square and;
    2. definition of;
    3. overview of;
    4. t test link;
    5. Type I errors and

U

  1. Undo command
  2. Unequal sample sizes: comparing;
    1. pooled variance for;
    2. t test conducted for
  3. Unequal variances
  4. Unexplained variance: explained variance versus;
    1. understanding
  5. UNICEF. See United Nations Children's Fund
  6. Uniform distributions
  7. United Nations Children's Fund (UNICEF)
  8. Unrelated data, t tests for

V

  1. #VALUE!
  2. Values
  3. =VAR ( ) function
  4. Variables: categorical;
    1. causal;
    2. caused;
    3. continuous numerical;
    4. definition of;
    5. discrete numerical;
    6. distinguishing;
    7. interval;
    8. as nominal;
    9. numerical;
    10. ordinal;
    11. overview of;
    12. pivot table with two;
    13. predictor;
    14. ratio;
    15. regression;
    16. regression analysis relating;
    17. as scale;
    18. simultaneous consideration of;
    19. statistics applying to;
    20. types of;
    21. x;
    22. y.
    23. See also Independence; specific variables
  5. Variances: assumption;
    1. calculating;
    2. as constant;
    3. definition of;
    4. as equal;
    5. error;
    6. estimated;
    7. examining;
    8. as explained;
    9. factorial analysis of;
    10. between group;
    11. within group;
    12. homogeneity of;
    13. as known;
    14. overview of;
    15. as pooled;
    16. regression;
    17. sample;
    18. standard error with;
    19. standard errors with estimated;
    20. standard errors with known;
    21. as total;
    22. as unequal;
    23. as unexplained.
    24. See also specific variances
  6. Variation: within ANOVA;
    1. SScols;
    2. SSrows;
    3. SSrows. cols;
    4. SST;
    5. SSWC.
    6. See also Residual variation
  7. =VARP ( ) function
  8. Vector

W

  1. Weighted least squares (WLS): definition of;
    1. dependent variable;
    2. example;
    3. in Excel;
    4. F statistic;
    5. interpreting;
    6. issues with;
    7. Logit compared with;
    8. Logit models and;
    9. for LPM estimation;
    10. OLS compared with;
    11. output;
    12. R square statistic;
    13. regression package and
  2. Weights: calculation;
    1. generation problem
  3. Within cell variation: calculating;
    1. dividing
  4. Within group variance (SSw): definition of;
    1. division of;
    2. overview of
  5. WLS. See Weighted least squares
  6. Women. See Breast cancer education
  7. Workbooks: definition of;
    1. overview of;
    2. spreadsheets as;
    3. worksheet inserted in
  8. Worksheet, workbook insertion of

X

  1. x axis
  2. x summations
  3. x variable
  4. XY(Scatter) chart

Y

  1. y axis
  2. y summations
  3. Yates's correction
  4. =YEARFRAC ( ) function
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