* 10 % Neukundenrabatt obendrauf*. Schnelle Lieferung in 1-2 Tagen. Rechnungskauf This is the so-called classical machine model and is based on the following assumptions: 1. P au =T au (so we neglect the error introduced by the power form of the swing equation, due to the fact that ω m≠ω R). 2. P m, the mechanical power into the machine, is constant. Therefore we consider that the governor is blocked, an Assumptions of the Classical Linear Regression Model Spring 2017 - StuDocu assumptions of the classical linear regression model the dependent variable is linearly related to the coefficients of the model and the model is correctl The following post will give a short introduction about the underlying assumptions of the classical linear regression model (OLS assumptions), which we derived in the following post. Given the Gauss-Markov Theorem we know that the least squares estimator and are unbiased and have minimum variance among all unbiased linear estimators Relaxing The Assumptions Of The Classical Model Last Updated on Wed, 06 Jan 2021 | Regression Models In Part I we considered at length the classical normal linear regression model and showed how it can be used to handle the twin problems of statistical inference, namely, estimation and hypothesis testing, as well as the problem of prediction

What are the classical assumptions? Why You Should Care About the Classical OLS Assumptions In a nutshell, your linear model should produce residuals that have a mean of zero, have a constant variance, and are not correlated with themselves or other variables. OLS is the most efficient linear regression estimator when the assumptions hold true ** When these classical assumptions for linear regression are true, ordinary least squares produces the best estimates**. However, if some of these assumptions are not true, you might need to employ remedial measures or use other estimation methods to improve the results. Many of these assumptions describe properties of the error term OLS is the best procedure for estimating a linear regression model only under certain assumptions. The word classical refers to these assumptions that are required to hold. Assumptions of the Classical Linear Regression Model: 1. The regression model is linear, correctly specified, and has an additive error term. 2

Classical Theory of Employment: Assumptions, Equation Model and Criticisms Propositions of Classical Theory of Employment:. Even at full employment, there may exist, voluntary unemployment,... Assumptions of the Theory:. Assumption of Full Employment:. Classical theory is based on the assumption of. THE ASSUMPTIONS OF ClASSICAl ECONOMICS. In previous chapters, we developed theories to explain what determines most important macroeconomic variables in the long run. Chapter 25 explained' the level and growth of productivity and real GDP. Chapters 26 and 27 explained how the financial system works and how the real interest rate adjusts to balance. ** ADVERTISEMENTS: In this article we will discuss about:- 1**. Assumptions of Classical Theory of Interest 2. Supply and Demand for Capital 3. Determination of Rate of Interest 4. Features of Classical Theory 5. Criticisms. The economists like Ricardo, J. S. Mill, Marshall and Pigou developed the, classical theory of interest which is also known as [ The classical statistical model is based on two assumptions, one about the data (or the source of the data) and the other about the behavior of the researcher. Describe them. asked Aug 14, 2019 in Statistics by Platini. introductory-statistics

Classical Linear Regression Model: Assumptions and Diagnostic Tests Yan Zeng Version 1.1, last updated on 10/05/2016 Abstract Summary of statistical tests for the Classical Linear Regression Model (CLRM), based on Brooks [1], Greene [5] [6], Pedace [8], and Zeileis [10]. Contents 1 The Classical Linear Regression Model (CLRM) Five assumptions relating to the classical linear regression model (CLRM) were made. the estimator technique, ordinary least squares (OLS), had a number of desirable properties, and, hypothesis tests regarding the coefficient estimates could validly be conducted

Chapter 5 classical linear regression model assumptions and diagnostic tests Don't use plagiarized sources. Get Your Custom Essay on Classical linear regression model assumptions Just from $10/Page Order Essay 5.1 introduction Five assumptions relating to the classical linear regression model (CLRM) were made. Also saw that: the estimator technique, ordinary least squares Continue reading. ** Classical model: It was the most desired model before the great depression, founded on the philosophies of Adam Smith**. It states that the economy has no restriction, and prices and wages are. We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings

In this chapter, we relax the assumptions made in Chapter 3 one by one and study the effect of that on the OLS estimator. In case the OLS estimator is no longer a viable estimator, we derive an alternative estimator and propose some tests that will allow us to check whether this assumption is violated The classical statistical model is based on two assumptions, one about the data (or the source of the data) and the other about the behavior of the researcher. Describe them. asked Aug 14, 2019 in Statistics by Platin Based on the assumptions of the classical model, all markets clear since prices are perfectly flexible and able to adjust until supply equals demand. This is also valid for the labour market. Under the classical model frame, an increase in the money supply, for instance, does not alter real variables like employment level or real wage In this video you will learn the introduction, features and assumptions of classical theory of income and employment in a classroom atmosphere. In this video..

This video discuss Gauss-Markov theorem, Central Limit Theorem and BLUE estimates.Important Note: OLS estimates remains BLUE even multicollinearity exist in. Chapter 5 classical linear regression model assumptions and diagnostic tests Don't use plagiarized sources. Get Your Custom Essay on Classical linear regression model assumptions Just from $13/Page Order Essay 5.1 introduction Five assumptions relating to the classical linear regression model (CLRM) were made. Also saw that: the estimator technique, ordinary least squares (OLS), had a number. The assumption of the classical linear regression model comes handy here. Let us assume that B0 = 0.1 and B1 = 0.5. Using these values, it should become easy to calculate the ideal weight of a person who is 182 cm tall. Weight = 0.1 + 0.5 (182) entails that the weight is equal to 91.1 kg

- In order to actually be usable in practice, the
**model**should conform to the**assumptions**of linear regression.**Assumption**1 The regression**model**is linear in parameters An example of**model**equation that is linear in parameter - The Classical Assumptions 1. The regression model is linear in the coefficients , correctly specified , and has an additive error term. 2. The error term has zero population mean : E(εi) = 0. 3. All independent variables are uncorrelated with the error term: Cov (Xi,εi) = 0 for each independent variable Xi . 4
- 7 classical assumptions of ordinary least squares 1. 7 Classical Assumptions of Ordinary Least Squares (OLS) Linear Regression By Jim Frost 38 Comments Ordinary Least Squares (OLS) is the most common estimation method for linear models—and that's true for a good reason

CHAPTER THREE: TWO-VARIABLE REGRESSION **MODEL** 95. 3.8. Spearman's rank correlation coefficient rs is defined as follows: where d = difference in the ranks assigned to the same individual or phenomenon and n = number of individuals or phenomena ranked. Derive rs from r defined in (3.5.13). Hint: Rank the X and Y values from 1 to n The classical model prescribes the best way to make decisions, based on four assumptions: a clearly defined problem, eliminated uncertainty, access to full information, and rational behavior of.

There is document - Classical Linear Regression Model Notation and Assumptions Model Estimation -Method of Moments -Least Squares -Partitioned Regression Model Interpretation available here for reading and downloading. Use the download button below or simple online reader If these assumptions hold, the OLS estimator is now also said to be Best, making it the Best Linear Unbiased Estimator (BLUE). In short, this means that there is no better estimator than the OLS for this particular model Classical Theory of Employment: Assumptions, Equation Model and Criticisms September 11, 2018 Classical Theory of Employment (Say's Law): Assumptions, Equation & Criticisms September 11, 2018 Before uploading and sharing your knowledge on this site, please read the following pages Assumptions of Classical Test Theory. Classical test theory assumes linearity—that is, the regression of the observed score on the true score is linear. This linearity assumption underlies the practice of creating tests from the linear combination of items or subtests. In addition, the following assumptions are often made by classical test.

Basics of Classical Test Theory Theory and Assumptions Types of Reliability Example Classical Test Theory Classical Test Theory (CTT) - often called the true score model Called classic relative to Item Response Theory (IRT) which is a more modern approach CTT describes a set of psychometric procedures used to test items and scale ADD ANYTHING HERE OR JUST REMOVE IT Facebook Twitter Pinterest linkedin Telegram. ACCOUN In general, based on the research by Robbins (2003), he summarized all the assumptions of classical decision making model illustrated in Chart 2. Robbins (2003) considered that all these assumptions are subjective and can not represent the real situation in the practice If you've compared two textbooks on linear models, chances are, you've seen two different lists of assumptions. I've spent a lot of time trying to get to the bottom of this, and I think it comes down to a few things. 1. There are four assumptions that are explicitly stated along with the model, and some authors stop there. 2 The Classical model is a representation of the relationship between employment, output, wages, and prices in the long run. Our plan is to first understand the pieces fth d l th fitth t th d Kathryn Dominguez, Winter 2010 6 of the model, then fit them together, and then look at how output is determined in the Classical model and what role there i

The model have to be linear in parameters, but it does not require the model to be linear in variables. Equation 1 and 2 depict a model which is both, linear in parameter and variables. Note that Equation 1 and 2 show the same model in different notation. (1) (2) In order for OLS to work the specified model has to be linear in parameters In fact, there were six basic assumptions about classical physics that indicated that the greater mysteries of the universe had either been solved or would proceed to be solved presently. These six assumptions about classical physics were historically thought to be absolutely true (contrastingly, today all six assumptions of classical physics have been challenged or proven to be unsupported by. 4. Normality: The residuals of the model are normally distributed. If one or more of these assumptions are violated, then the results of our linear regression may be unreliable or even misleading. In this post, we provide an explanation for each assumption, how to determine if the assumption is met, and what to do if the assumption is violated

We consider the classical regression model defined by a random vector X n×1, scalar matrices y n×m, v n×n, a scalar column b m×1 and a scalar s 2 satisfying EX = yb, Cov X = s 2 v and the usual regularity conditions. Using only assumptions, we prove that the classical estimator s ̂ 2 for s 2 in that model is the unique unbiased one with minimum variance in a large class of estimators Classical Test Theory Assumptions, Equations, Limitations, and Item Analyses C lassical test theory (CTT) has been the foundation for measurement theory for over 80 years. The conceptual foundations, assumptions, and extensions of the basic premises of CTT have allowed for the development of some excellent psychometrically sound scales Classical Approach to Decision Making. Classical approach is also known as prescriptive, rational or normative model. It specifies how decision should be made to achieve the desired outcome. Under classical approach, decisions are made rationally and directed toward a single and stable goal All of the following are assumptions of the classical model EXCEPT A) inflexible wages. B) absence of money illusion. C) pure competition. D) self-interest of economic actors Classical linear regression model. The classical model focuses on the finite sample estimation and inference, meaning that the number of observations n is fixed. This contrasts with the other approaches, which study the asymptotic behavior of OLS, and in which the number of observations is allowed to grow to infinity

- To fit the model to n data-points, we would select a, b , and to maximize log-likelihood: Once we have estimated the parameters, we can measure the amount of inefficiency for each observation, i. Violations of Classical Linear Regression Assumptions.
- model from there, which became known as the \classical risk model. Since his in-troduction, much work has been done to better model risk through complications of the model such as including interest, operating costs, and generalizing Lundberg's assumptions. The biggest advancement to ruin theory after Lundberg and Cram e
- g zero conjectural variation on the part of the duopolists (oligopolists), classical models ignore the mutual interdependence which is the chief characteristic of oligopoly. Thus, classical models provide solution for oligopoly problem by removing from it is most important feature. 4. Chamberlin's Oligopoly Model

Home Uncategorized what are the assumptions of classical linear regression model. Search. Recent Posts. what are the assumptions of classical linear regression model; How do I find a network pharmacy? New techni for reducing risk; what are the assumptions of classical linear regression model DOI: 10.1017/cbo9781139540872.006 Corpus ID: 164214345. Classical Linear Regression Model : Assumptions and Diagnostic Tests @inproceedings{Zeng2016ClassicalLR, title={Classical Linear Regression Model : Assumptions and Diagnostic Tests}, author={Y. Zeng}, year={2016}

-The Classical Model o Assumptions: Pure competition exists Wages and prices are flexible People act on their own self interest People don't ha ve money illusion, meaning that they understand nominal vs. real value Problems in the economy are temporary and will correct themselves • Classical assumptions test isn't needed in linear regression that use to count a value in a variable. For example, counting stock return use market model. 5 Types Test. 1. • Regression model should have residual variance similarity between a odservation whith oter observation (homoskedastic) K) in this model. 2.2 Assumptions The classical linear regression model consist of a set of assumptions how a data set will be produced by the underlying 'data-generating process.' The assumptions are: A1. Linearity A2. Full rank A3. Exogeneity of the independent variables A4. Homoscedasticity and nonautocorrelation A5. Data generation A6.

• Classical approach important in justice policy during the 19th century, but became of less interest to criminologists at the end of the 19th century. • Beginning in the mid-1970s, a resurgence in interest in the classical approach. Rehabilitation approach came under attack from conservative citizens and politicians. Rational actor models What is it?<br />The standard, or neo-classical, economic model is the dominant framework for thinking about consumer welfare and consumer choice.<br />It is what you will learn in any introductory microeconomics course.<br /> 3. Assumptions of the Standard Economic Model of Consumer Behavior<br />People have known preferences. <br /> 4 A model that closely mimics the real environment of most managers and decision makers is the political model. a. normative b. administrative c. descriptive d. classical e. political 57. All of these are basic assumptions of the political model EXCEPT a. organizations are made up of groups with diverse interests, goals, and values

Linear regression models are extremely useful and have a wide range of applications. When you use them, be careful that all the assumptions of OLS regression are satisfied while doing an econometrics test so that your efforts don't go wasted. These assumptions are extremely important, and one cannot just neglect them Round-Optimal Blind Signatures in the Plain Model from Classical and Quantum Standard Assumptions Shuichi Katsumata and Ryo Nishimaki and Shota Yamada and Takashi Yamakawa Abstract: Blind signatures, introduced by Chaum (Crypto'82), allows a user to obtain a signature on a message without revealing the message itself to the signer

Corpus ID: 21912435. Relaxing the assumptions in the linear classical model @inproceedings{UrielRelaxingTA, title={Relaxing the assumptions in the linear classical model}, author={E. Uriel} Therefore, neo-classical economists interested in markets under disequilibrium conditions construct their model to include an eventual, long run equilibrium position towards which the market is moving, even if it never actually arrives! 6) Many participants, Freedom of Entry and Exit: These assumptions ensure that a market is freely competitive ** ADVERTISEMENTS: EOQ: Economic Ordering Quantity Model (Assumptions and Determination of EOQ)! One of the important decisions to be taken by a firm in inventory management is how much to buy at a time, or say, for how much inventory to place order at a time**. This is called 'Economic Ordering Quantity.' In fact, EOQ gives [ Solow model is neo-classical in character, and it is evident from Solow's own comments: I have been deliberately as neo-classical as you can get. Solow's model is a synthesis of the classical and modern views. This model retains the basic assumptions of the classical model i.e., existence of full employment and perfect competition etc. CLRM stands for the Classical Linear Regression Model. The CLRM is also known as the standard linear regression model. Three sets of assumptions define the multiple CLRM -- essentially the same three sets of assumptions that defined the simple CLRM, with one modification to assumption A8. 1. Assumptions respecting the formulation of the.

Part IV Violations of Classical Regression Model Assumptions For a veritable crash course in econometrics basics, including an easily absorbed rundown of the three most common estimation problems, access this - Selection from Econometrics For Dummies [Book Assumptions of EOQ model. If the economic order quantity model is applied, the following assumptions should be met: The rate of demand is constant, and total demand is known in advance. The ordering cost is constant. The unit price of inventory is constant, i.e., no discount is applied depending on order quantity Questioning what the required assumptions of a statistical model are without this context will always be a fundamentally ill-posed question. We're going to spend a good deal of time diving into the OLS estimator, learning about it's properties under different conditions, and how it relates to other estimators

Classical Linear Regression Model listed as CLRM. Classical Linear Regression Model - How is Classical Linear Regression Model abbreviated? https://acronyms.thefreedictionary chapters cover the classical linear regression model, classical linear regression model assumptions and diagnostic tests, univariate time series modeling and. * Those fundamental assumptions include the following: 1*. People have rational preferences among outcomes. 2. Individuals maximize utility and firms maximize profits. 3. People act independently on the basis of full and relevant information. Theories based on, or guided by, these assumptions are neoclassical theories Of course, Python does not stay behind and we can obtain a similar level of details using another popular library — statsmodels.One thing to bear in mind is that when using linear regression in statsmodels we need to add a column of ones to serve as intercept. For that I use add_constant.The results are much more informative than the default ones from sklearn

- ed through a hypothetical maximization of utility by income-constrained individuals and of profits by firms facing production costs and.
- One of the assumptions of the classical linear regression model CLRM Assumption 9 is that the regression model used in the analysis is correctly specified I
- The goal of the present work is to evaluate the impact of all the assumptions used widely in the models based in the ε-NTU methodology. The paper includes a presentation of the numerical scheme, model validation, and a parametric study which tests the impact of the traditional heat exchanger model assumptions applied for a microchannel gas cooler with CO2 as working fluid
- Assumptions of the Say's Law of Market: The classical model is based mainly on the following four assumptions: (i) Pure competition exists. No single buyer or seller of commodity or an input can affect its price. (ii) Wages and prices are flexible. The wages and prices of goods are free to move to whatever level the supply and demand dictate
- Classical Linear Regression Model Assumptions and Diagnostic Tests 2021 Questions and Answers with Explanations STUDY MODE Questions and Answers latest Update 100% Correct Download to Score
- Identify and evaluate assumptions. Follow an argument to its conclusion. Spot contradictions and faulty logic. Draw appropriate distinctions. Avoid extremes. Exercise foresight. Three basic tools for developing practical wisdom in the classical model: Syllogistic logic (to identify assumptions and follow an argument) dialectic (to spot.

* Discuss the assumptions that underlie the classical model of decision-making, and explain how this model would help to explain the behavior of a manager who was attempting to act consistently with this model in a realistic business situation of your choosing*. Show More. Show Less On Stuvia you will find the most extensive lecture summaries written by your fellow students. Avoid resits and get better grades with material written specifically for your studies

There are four principal assumptions which justify the use of linear regression models for purposes of inference or prediction: (i) linearity and additivity of the relationship between dependent and independent variables: (a) The expected value of dependent variable is a straight-line function of each independent variable, holding the others fixed Assumptions that underlie the classical models of decisions 1. Devil's advocacy can be a safeguard against costly mistakes. However, it can also hamper decision making. How can... 2. Discuss the assumptions that underlie the classical model of decision-making, and explain how this model would.

- It has to be noted that the Fin2D model is employed to assess the impact of the a consequence of a wrong prediction of the individual tube classical heat exchanger modelling assumptions on the capacity introduces a wrong evaluation of the fluid properties accuracy of the performance predictions for such conditions. at the tube outlet section
- ed primarily as a location in a norm group.people and items are placed.
- These
**assumptions**de-ne the**classical**errors-in-variables**model**. Substitute (2) into (1): y = (xe u)+ = y Multivariate**Models**Return to OLS estimation in a simple cross-section and consider what happens to the bias as we add more variables to the**model**. Consider the equatio

- Such theories have left traces in the macroeconomic modelling area, so that, in 1776, we find the classical model of Smith, which, based on the results obtained at microeconomic level, analyses the labour demand and supply, as fundamental equilibrium, then, in 1870, the classical general equilibrium model of Walras, describing the economy by the aggregation of the individualsâ€™ behaviours
- al money prices rather than to relative prices. C)people are motivated by self-interest. D)wages and prices are flexible
- Bohr's Atomic Model was introduced by Niels Bohr in 1915. It was basically a modified version of Rutherford's Atomic Model wherein Bohr explained that electrons move in fixed orbitals (shells) and not anywhere in between and he also explained that each orbit (shell) has a fixed energy level
- al money prices rather than to relative prices. C) people are motivated by self-interest. D) wages and prices are flexible
- Definition. Model Assumptions denotes the large collection of explicitly stated (or implicit premised), conventions, choices and other specifications on which any Risk Model is based. The suitability of those assumptions is a major factor behind the Model Risk associated with a given model.. Context. In the context of modelling economic, financial or other complex systems, model assumptions.
- assumptions of classical true score model (2) Bloom Taxonomy (1) coefficient of equivalence (1) coefficient of stability (1) construct validity (2) constructs (3) Content Analysis (1) content validity (1) convergent validity (2) correlation (1) covariance (1) criterion-related validity (1) critical incidents (1) cronbach's alpha (2.
- statistical model are ensured. When such assumptions are violated, procedures must be applied to remedy the problem. The present study aimed to compare and investigate how the assumptions of the statistical model can be achieved by classical linear model and generalized linear mixed model, as well as their impact on the hypothesis test of the.

The classical linear regression model assumes X to be fixed, so there would be no joint distribution? $\endgroup$ - Majte Mar 22 '13 at 22:09 1 $\begingroup$ X does not need to be fixed in the classical linear regression Classical Linear Model (CLM) Assumptions: The ideal set of assumptions for multiple regression analysis. The assumptions include linearity in the parameters, no perfect collinearity, the zero conditional mean assumption, homoskedasticity, no serial correlation, and normality of the errors The classical model of decision making works under the assumption that decision makers or managers have complete set of information, Discuss the assumptions that underlie the classical and administrative decision making models. Which model more closely aligns with you work and/or management style

The LibreTexts libraries are Powered by MindTouch ® and are supported by the Department of Education Open Textbook Pilot Project, the UC Davis Office of the Provost, the UC Davis Library, the California State University Affordable Learning Solutions Program, and Merlot. We also acknowledge previous National Science Foundation support under grant numbers 1246120, 1525057, and 1413739 They are not connected. 2.2 Assumptions The classical linear regression model consist of a set of assumptions how a data set will be produced by the underlying â data-generating process.â The assumptions are: A1. If the coefficient of Z is 0 then the model is homoscedastic, but if it is not zero, then the model has heteroskedastic errors. K) in this model. . The importance of OLS assumptions. assumptions, classical economics: Classical economics, especially as directed toward macroeconomics, relies on three key assumptions--flexible prices, Say's law, and saving-investment equality. Flexible prices ensure that markets adjust to equilibrium and eliminate shortages and surpluses

- Click on the button. This will generate the output.. Stata Output of linear regression analysis in Stata. If your data passed assumption #3 (i.e., there was a linear relationship between your two variables), #4 (i.e., there were no significant outliers), assumption #5 (i.e., you had independence of observations), assumption #6 (i.e., your data showed homoscedasticity) and assumption #7 (i.e.
- ation Theory predicts the behavior of the la
- Assessing Classical Test Assumptions . In classical parametric procedures we often assume normality and constant variance for the model error term
- Classic models of population dynamics: assumptions about self-regulative mechanisms and numbers of interactions between individual

Assumptions of Linear regression needs at least 2 variables of metric (ratio or interval) scale. While a scatterplot allows you to check for autocorrelations, you can test the linear regression model for autocorrelation with the Durbin-Watson test Though this model has been proven to be better than the traditional model, this model adopts assumptions that can hardly be expected to be fulfilled. Recommended Articles. This has been a guide to what is the Heckscher-Ohlin Model and its definition. Here we discuss components, assumptions, institutions, an example of the h-o model However, there are many critiques of the neo-classical model, arguing economics is more complex with issues of market failure and irrational behaviour. Pre-classical microeconomic theory Before, Adam Smith, economics was more disparate with no commanding overall theory Classic assumptions of OLS models In this article, the attention shifts to linear models in particular linear regression models estimated via OLS. Linear regression models are estimated based on certain underlying assumptions commonly referred to the Gauss-Markov assumptions for simple regression

Linear regression (Chapter @ref(linear-regression)) makes several assumptions about the data at hand. This chapter describes regression assumptions and provides built-in plots for regression diagnostics in R programming language.. After performing a regression analysis, you should always check if the model works well for the data at hand When studying the classical linear regression model, one necessarily comes across the Gauss-Markov Theorem. The Gauss-Markov Theorem is a central theorem for linear regression models. It states different conditions that, when met, ensure that your estimator has the lowest variance among all unbiased estimators. More formally, the Gauss-Markov Theorem tells us that in a regressio An in-depth discussion of pore formation is presented in this paper by first reinterpreting in situ observations reported in the literature as well as assumptions commonly made to model pore formation in aluminum castings. The physics of pore formation is reviewed through theoretical fracture pressure calculations based on classical nucleation theory for homogeneous and heterogeneous. The Solow Growth Model is an exogenous model of economic growth that analyzes changes in the level of output in an economy over time as a result of changes in the population Demographics Demographics refer to the socio-economic characteristics of a population that businesses use to identify the product preferences and growth rate, the savings rate, and the rate of technological progress

before hypothesis testing in forecast modelling The fitted model is said to be adequate if it explains the data set adequately, i.e., if the residual does not contain (or conceal) any 'explainable non-randomness' left from the ('explained') model. i.e. if the residual is purely random/white noise If all the OLS assumptions are satisfied Assumptions of Multiple Linear Regression. Multiple linear regression analysis makes several key assumptions:. There must be a linear relationship between the outcome variable and the independent variables. Scatterplots can show whether there is a linear or curvilinear relationship Start studying Chapter 8: The Classical Long Run Model. Learn vocabulary, terms, and more with flashcards, games, and other study tools