A guide to using Microsoft Excel for Windows 95 for statistical analysis in business. With a step-by-step approach and the use of numerous screen shots, the book is intended even for students who have no previous experience of computer spreadsheets.
Reihe
Auflage
Sprache
Verlagsort
Verlagsgruppe
Zielgruppe
Für höhere Schule und Studium
Für Beruf und Forschung
Editions-Typ
Illustrationen
illustrations, bibliography, index
Maße
Höhe: 241 mm
Breite: 184 mm
Gewicht
ISBN-13
978-0-534-52929-1 (9780534529291)
Copyright in bibliographic data is held by Nielsen Book Services Limited or its licensors: all rights reserved.
Schweitzer Klassifikation
Part 1 Getting started: accessing the student files; launching Excel; using the Excel window; opening an Excel window; using the worksheet window; formulas and functions; printing worksheets; saving your work; exiting Excel. Part 2 Entering and manipulating data: entering data; defining range names; cell references; inserting new data; sorting data; querying data; importing data from a text file; creating new variables; freeze planes. Part 3 Single variable graphs and statistics: statistics and distributions; frequency tables and histograms; statistics describing a distribution; boxplots; distribution shapes; other descriptive statistics; Part 4 Scatterplots: creating scatterplots with the chart wizard; editing a chart; working with the data series; plotting several Y's; plotting two variables with a grouping variable; scatterplot matrices. Part 5 Probability distributions: random variables; probability distributions; normal data; the normal probability plot (PPlot); the distribution of the sample mean; the central-limit theorem. Part 6 Statistical inference: confidence intervals; hypothesis testing; the T distribution; paired comparisons; two sample comparisons. Part 7 Tables: variable types - continuous and categorical; pivot tables; pie charts; bar charts; two-way tables; the chi-square distribution; computing expected values; Pearson chi-square statistic; validity of chi-square test with small frequencies; tables with ordinal values. Part 8 Correlation and simple regression: simple linear regression; correlation; regression analysis with Excel; correlation and plot matrices; graphing relationships. Part 9 Multiple regression: regression models; the F distribution; regression assumptions; using regression for prediction; regression example - predicting grades; useful plots; regression example - sex discrimination. Part 10 Analysis of variance: one-way analysis of variance; multiple comparisons - Bonferroni test; one-way analysis of variance; two-way analysis of variance. Part 11 Time series: time-series concepts; the Dow in the '80s; lagged values; the autocorrelation function; simple exponential smoothing and forecasting; two-parameter exponential smoothing; seasonality; seasonal example - beer production; three-parameter exponential smoothing; optimizing the exponential smoothing. Part 12 Quality control: statistical quality control; control charts; the mean chart when sigma is known; the mean chart when sigma is unknown; the range chart; the C-chart; the P-chart; the Pareto chart.