FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W71556688> ?p ?o ?g. }

• W71556688 startingPage "89" @default.
• W71556688 abstract "ABSTRACT LOTUS 1-2-3 provides many powerful tools, including linear regression, to managers. Unfortunately, 1-2-3's regression is not useful in situations where the dependent variables are binary or either/or. This article illustrates situations which have binary outcomes and shows how regression based on logarithms, called LOGIT, can yield managerially useful results. The article provides a simple method of making the necessary computations with LOTUS 1-2-3. A free LOTUS 1-2-3 program is offered to readers. INTRODUCTION Linear regression is a powerrful, well-known, and commonly used analytical technique in business; LOTUS 1-2-3 permits managers to use regression in many situations. The purpose of this article is to extend the usefulness of 1-2-3 by broadening the situations in which regression can be used. The methods explained here put a powerful new tool in the hands of managers. That tool should be particularly useful to small business managers, entrepreneurs, and other managers who are comfortable in LOTUS and do not want to purchase statistical packages such as SPSS-PC and SAS-PC. First, the concepts of linear regression are reviewed using an intuitive approach. second, the importance of situations in which the dependent variable is binary (either/or) is explained and the inapplicability of 1-2-3's solution to those situations is illustrated. LOGIT regression, an approach to the binary problem, is introduced. Finally, a LOTUS 1-2-3 program which incorporates LOGIT regression is offered free of charge to readers. Use of the offered program will allow managers to use LOGIT without investing large sums in SAS, SPSS, or other muscle statistical packages. LINEAR REGRESSION Properly applied, linear regression often permits managers to make sense out of a mass of data and to reduce the data to a simple equation. This simplification makes the data more readily understandable and permits managers to make inferences about the relationships between dependent and independent variables. It is also used to make inferences about what will happen if of the variables affecting a situation changes. Consider the data shown in Table 1. The lot size produced appears to vary with the number of man-hours worked. The strength of the relationship, however, is unquantified. Further, has no idea how much of the variance in lot size is explained by changes in man-hours. Table 1's data is plotted on the scatterplot in Figure la, where each dot represents observation. It can be seen that the dots suggest a straight line. Some important pieces of information can be developed if the dependent variable (lot size) is regressed on the independent variable (number of manhours): (1) the regression equation, (2) a test of statistical significance, and (3) r^sup 2^. The regression equation is the formula for the and straight line, shown in Figure lb, which best approximates or describes the data. This one and only line is reason that linear regression is so powerful and so commonly used; it permits the manager to express a large number of observations as a single equation. As an added benefit, the regression equation is in the form of a formula for a straight line so the line can be graphed to develop simple and straightforward visual aids. The regression equation is in the form1 of Y = β^sub 1^ + β^sub 2^X where Y = the dependent variable, β^sub 1^ = the intercept; some constant which is the numerical value of the point where the regression line cuts the vertical axis, β^sub 2^ = the slope of the regression line, and X = the independent variable. Significance indicates whether the independent variable has a statistically significant impact on the dependent variable. The significance is usually the first item examined when interpreting the results of linear regression. It is often expressed as a confidence level, e.g. 95% confidence. If it is found that the desired statistical significance does not exist, no further interpretation is appropriate because the results could have been obtained merely by chance. …" @default.
• W71556688 created "2016-06-24" @default.
• W71556688 creator A5000075816 @default.
• W71556688 creator A5026325301 @default.
• W71556688 creator A5053583771 @default.
• W71556688 date "1992-07-01" @default.
• W71556688 modified "2023-09-24" @default.
• W71556688 title "LOGIT Regression Analysis Using LOTUS 1-2-3" @default.
• W71556688 hasPublicationYear "1992" @default.
• W71556688 type Work @default.
• W71556688 sameAs 71556688 @default.
• W71556688 citedByCount "0" @default.
• W71556688 crossrefType "journal-article" @default.
• W71556688 hasAuthorship W71556688A5000075816 @default.
• W71556688 hasAuthorship W71556688A5026325301 @default.
• W71556688 hasAuthorship W71556688A5053583771 @default.
• W71556688 hasConcept C105795698 @default.
• W71556688 hasConcept C119857082 @default.
• W71556688 hasConcept C120068334 @default.
• W71556688 hasConcept C140331021 @default.
• W71556688 hasConcept C149782125 @default.
• W71556688 hasConcept C151956035 @default.
• W71556688 hasConcept C152877465 @default.
• W71556688 hasConcept C27574286 @default.
• W71556688 hasConcept C32224588 @default.
• W71556688 hasConcept C33923547 @default.
• W71556688 hasConcept C41008148 @default.
• W71556688 hasConcept C48921125 @default.
• W71556688 hasConcept C57381214 @default.
• W71556688 hasConcept C83546350 @default.
• W71556688 hasConceptScore W71556688C105795698 @default.
• W71556688 hasConceptScore W71556688C119857082 @default.
• W71556688 hasConceptScore W71556688C120068334 @default.
• W71556688 hasConceptScore W71556688C140331021 @default.
• W71556688 hasConceptScore W71556688C149782125 @default.
• W71556688 hasConceptScore W71556688C151956035 @default.
• W71556688 hasConceptScore W71556688C152877465 @default.
• W71556688 hasConceptScore W71556688C27574286 @default.
• W71556688 hasConceptScore W71556688C32224588 @default.
• W71556688 hasConceptScore W71556688C33923547 @default.
• W71556688 hasConceptScore W71556688C41008148 @default.
• W71556688 hasConceptScore W71556688C48921125 @default.
• W71556688 hasConceptScore W71556688C57381214 @default.
• W71556688 hasConceptScore W71556688C83546350 @default.
• W71556688 hasIssue "2" @default.
• W71556688 hasLocation W715566881 @default.
• W71556688 hasOpenAccess W71556688 @default.
• W71556688 hasPrimaryLocation W715566881 @default.
• W71556688 hasRelatedWork W121902686 @default.
• W71556688 hasRelatedWork W1592335992 @default.
• W71556688 hasRelatedWork W169070958 @default.
• W71556688 hasRelatedWork W2004042461 @default.
• W71556688 hasRelatedWork W2037513635 @default.
• W71556688 hasRelatedWork W2104851540 @default.
• W71556688 hasRelatedWork W23150098 @default.
• W71556688 hasRelatedWork W2329990193 @default.
• W71556688 hasRelatedWork W2332086153 @default.
• W71556688 hasRelatedWork W2334305926 @default.
• W71556688 hasRelatedWork W245810865 @default.
• W71556688 hasRelatedWork W26220364 @default.
• W71556688 hasRelatedWork W2994431069 @default.
• W71556688 hasRelatedWork W3000408780 @default.
• W71556688 hasRelatedWork W3020921722 @default.
• W71556688 hasRelatedWork W3038531720 @default.
• W71556688 hasRelatedWork W3152564884 @default.
• W71556688 hasRelatedWork W318761033 @default.
• W71556688 hasRelatedWork W80642230 @default.
• W71556688 hasRelatedWork W2597505048 @default.
• W71556688 hasVolume "4" @default.
• W71556688 isParatext "false" @default.
• W71556688 isRetracted "false" @default.
• W71556688 magId "71556688" @default.
• W71556688 workType "article" @default.