9780803951280 - Regression with Dummy Variables: 93 (Quantitative Applications in the Social Sciences) de Hardy, Melissa A (16 resultados)

Condición: New. In.

Paperback. Condición: New. Social scientists are often interested in studying differences in groups, such as gender or race differences in attitudes, buying behaviors, or socioeconomic characteristics. When the researcher seeks to estimate group differences through the use of independent variables that are qualitative (i.e., measured at only the nominal level), dummy variables will allow the researcher to represent information about group membership in quantitative terms without imposing unrealistic measurement assumptions on the categorical variables. Beginning with the simplest model, Hardy probes the use of dummy variable regression in increasingly complex specifications, exploring issues such as: interaction, heteroscedasticity, multiple comparisons and significance testing, the use of effects or contrast coding, testing for curvilinearity, and estimating a piecewise linear regression.

Paperback. Condición: New. New Paperback! Pristine unmarked pages, may have very slight warehouse wear, no remainder marks, still a great buy straight from warehouse, sealed in plastic, exact artwork as listed,

Paperback. Condición: New. Social scientists are often interested in studying differences in groups, such as gender or race differences in attitudes, buying behaviors, or socioeconomic characteristics. When the researcher seeks to estimate group differences through the use of independent variables that are qualitative (i.e., measured at only the nominal level), dummy variables will allow the researcher to represent information about group membership in quantitative terms without imposing unrealistic measurement assumptions on the categorical variables. Beginning with the simplest model, Hardy probes the use of dummy variable regression in increasingly complex specifications, exploring issues such as: interaction, heteroscedasticity, multiple comparisons and significance testing, the use of effects or contrast coding, testing for curvilinearity, and estimating a piecewise linear regression.

PF. Condición: New.

Condición: New.

Condición: New.

Condición: New. pp. 96 1st Edition.

Paperback. Condición: new. Paperback. It is often necessary for social scientists to study differences in groups, such as gender or race differences in attitudes, buying behaviour, or socioeconomic characteristics. When the researcher seeks to estimate group differences through the use of independent variables that are qualitative, dummy variables allow the researcher to represent information about group membership in quantitative terms without imposing unrealistic measurement assumptions on the categorical variables. Beginning with the simplest model, Hardy probes the use of dummy variable regression in increasingly complex specifications, exploring issues such as: interaction, heteroscedasticity, multiple comparisons and significance testing, the use of effects or contrast coding, testing for curvilinearity and estimating a piecewise linear regression. Social scientists are often interested in studying differences in groups, such as gender or race differences in attitudes, buying behaviors, or socioeconomic characteristics. When the researcher seeks to estimate group differences through the use of independent variables that are qualitative (i.e., measured at only the nominal level), dummy variables will allow the researcher to represent information about group membership in quantitative terms without imposing unrealistic measurement assumptions on the categorical variables. Beginning with the simplest model, Hardy probes the use of dummy variable regression in increasingly complex specifications, exploring issues such as: interaction, heteroscedasticity, multiple comparisons and significance testing, the use of effects or contrast coding, testing for curvilinearity, and estimating a piecewise linear regression. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Paperback. Condición: new. Paperback. It is often necessary for social scientists to study differences in groups, such as gender or race differences in attitudes, buying behaviour, or socioeconomic characteristics. When the researcher seeks to estimate group differences through the use of independent variables that are qualitative, dummy variables allow the researcher to represent information about group membership in quantitative terms without imposing unrealistic measurement assumptions on the categorical variables. Beginning with the simplest model, Hardy probes the use of dummy variable regression in increasingly complex specifications, exploring issues such as: interaction, heteroscedasticity, multiple comparisons and significance testing, the use of effects or contrast coding, testing for curvilinearity and estimating a piecewise linear regression. Social scientists are often interested in studying differences in groups, such as gender or race differences in attitudes, buying behaviors, or socioeconomic characteristics. When the researcher seeks to estimate group differences through the use of independent variables that are qualitative (i.e., measured at only the nominal level), dummy variables will allow the researcher to represent information about group membership in quantitative terms without imposing unrealistic measurement assumptions on the categorical variables. Beginning with the simplest model, Hardy probes the use of dummy variable regression in increasingly complex specifications, exploring issues such as: interaction, heteroscedasticity, multiple comparisons and significance testing, the use of effects or contrast coding, testing for curvilinearity, and estimating a piecewise linear regression. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Paperback. Condición: new. Paperback. It is often necessary for social scientists to study differences in groups, such as gender or race differences in attitudes, buying behaviour, or socioeconomic characteristics. When the researcher seeks to estimate group differences through the use of independent variables that are qualitative, dummy variables allow the researcher to represent information about group membership in quantitative terms without imposing unrealistic measurement assumptions on the categorical variables. Beginning with the simplest model, Hardy probes the use of dummy variable regression in increasingly complex specifications, exploring issues such as: interaction, heteroscedasticity, multiple comparisons and significance testing, the use of effects or contrast coding, testing for curvilinearity and estimating a piecewise linear regression. Social scientists are often interested in studying differences in groups, such as gender or race differences in attitudes, buying behaviors, or socioeconomic characteristics. When the researcher seeks to estimate group differences through the use of independent variables that are qualitative (i.e., measured at only the nominal level), dummy variables will allow the researcher to represent information about group membership in quantitative terms without imposing unrealistic measurement assumptions on the categorical variables. Beginning with the simplest model, Hardy probes the use of dummy variable regression in increasingly complex specifications, exploring issues such as: interaction, heteroscedasticity, multiple comparisons and significance testing, the use of effects or contrast coding, testing for curvilinearity, and estimating a piecewise linear regression. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Paperback / softback. Condición: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 147.

Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. &Uumlber den AutorRESEARCH aND TEACHING INTERESTSQuantitative Analysis Techniques, Longitudinal Methods Aging & Social ChangePublic Policy and Aging.Social Inequality, Social Sciences and Humanities Research Council of Canada. W.

Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - It is often necessary for social scientists to study differences in groups, such as gender or race differences in attitudes, buying behaviour, or socioeconomic characteristics. When the researcher seeks to estimate group differences through the use of independent variables that are qualitative, dummy variables allow the researcher to represent information about group membership in quantitative terms without imposing unrealistic measurement assumptions on the categorical variables. Beginning with the simplest model, Hardy probes the use of dummy variable regression in increasingly complex specifications, exploring issues such as: interaction, heteroscedasticity, multiple comparisons and significance testing, the use of effects or contrast coding, testing for curvilinearity and estimating a piecewise linear regression.

Condición: New. Print on Demand pp. 96.

Condición: New. PRINT ON DEMAND pp. 96.