ECON 010 Chapter Notes - Chapter 12: Simple Linear Regression, Scatter Plot, Regression Analysis

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brownantelope443

13 Jul 2018

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Professor jason lee: simple linear regression model. Oftentimes we are interested in the relationship between two variables. For example, a marketing manager is interested in the relationship between advertising spending and sales. The manager would be interested in the ability to predict sales volume based on a given level of advertising spending. If data can be obtained, a statistical procedure known as regression analysis can be used to develop an equation showing the relationship of variables. In regression analysis there are two key variables: a dependent variable and independent variables. Definition: a dependent variable is the variable that is being predicted (the variable of interest). Definition: independent variables are variables whose values are used to predict values of the dependent variable. For example, the marketing manager is interested in predicting the volume of sales making sales the dependent variable. Since the manager is using advertising expenditure to predict sales, advertising expenditure will be the independent variable.

Related Questions

ECON 3050

Q24. The coefficient of determination (r²) is calculated as 0.49, then the correlation coefficient:

Cannot be determined without the data

Should be - 0.70 or 0.70

Should be 0.

Neither of the above

Q25. A regression line is used for all of the following except one. Which one is not a valid use of a regression line?

To estimate the average value of Y at a specified value of X.

To predict the value of Y for an individual, given that individual's X-value.

To estimate the change in Y for a one-unit change in X.

To determine if a change in X causes a change in Y.

Q26. Which choice is not an appropriate description of YË in a regression equation?

Estimated response

Predicted response

Estimated average response

Observed response

Q27. Which of the following is the best way to determine whether or not there is a statistically significant linear relationship between two quantitative variables?

Compute a regression line from a sample and see if the sample slope is 0.

Compute the correlation coefficient and see if it is greater than 0.5 or less than â0.5.

Conduct a test of the null hypothesis that the population slope is 0.

Conduct a test of the null hypothesis that the population intercept is 0.

Q28. There is no relationship between variables unless the data points lie in a straight line.

True

False

Q29. The sample regression analysis

Is the same as the population regression line

Is used to estimate the population regression line

Shows the true relation between dependent and independent variables

None of the above.

Q30. In regression, a dependent variable is sometimes called a predictor variable.

True

False

Q31. In a linear regression equation of the form y = a + bx, the intercept shows

The amount that y changes when x changes by one unit

The amount that x changes when y changes by one unit

The value of y when x is zero

The value of x when y is zero.

Q32. In a linear regression equation of y = a + bx, the slope b shows

Y / b

X / b

Y / X

X / Y

yellowturtle964

Question 1

Which of the following approaches to understanding and predicting consumer behavior depends primarily on the knowledge and experience of a firm's employees and its suppliers?

		Test marketing and price experiments
		Analysis of historical data.
		Direct consumer surveys.
		Expert opinion.

Question 2

In which of the following situations would reliance on expert opinion as a basis for a managerial decision be most preferred?

		When the product being marketed is relatively new.
		When the level of economic activity can have a significant effect on the demand for the firm's output.
		When the product can be packaged with a variety of price and quality combinations.
		When the business in question serves as a supplier of inputs to other businesses, especially in multi-product situations where other strategies may be prohibitively expensive.

Question 3

The approach to analyzing consumer behavior that asks consumers to rank and choose among different product attributes to reveal their relative valuation of different characteristics is called:

		conjoint analysis.
		contingent valuation.
		the hedonic estimation technique.
		a direct consumer survey.

Question 4

All of the following are limitations of direct consumer surveys except:

		the possibility of response biases because survey respondents may not want to reveal their true preferences.
		the possibility that the type of questions asked may unintentionally bias the respondent's answers.
		the likelihood that respondents will deliberately and systematically mislead interviewers.
		the possibility that consumers' responses may not reflect their actual behavior in the market place.

Question 5

Which of the following approaches to understanding and predicting consumer behavior does not actually solicit any information from potential customers?

		Expert opinion.
		Test marketing.
		Analysis of historical data.
		Conjoint analysis.

Question 6

Data collected on a sample of individuals with different characteristics at a specific point in time are called:

		panel data.
		cross-section data.
		time series data.
		none of the above.

Question 7

Which of the following approaches to understanding and predicting consumer behavior provides the most insight into how consumers can be expected to respond in an actual market setting?

		Test marketing.
		Conjoint analysis.
		Expert opinion.
		Analysis of historical data.

Question 8

An approach to analyzing consumer behavior in which consumer reaction to different prices is analyzed in a laboratory situation or a test market is called:

		non-price experiments.
		focus groups.
		price experiments.
		none of the above.

Question 9

Data collected on the same observation unit at a number of points in time are called:

		panel data.
		time series data.
		cross-section data.
		none of the above.

Question 10

A measure of how much the coefficient would vary in regressions based on different samples is called:

		F-statistic.
		standard error of the estimated coefficient.
		t-statistic.
		partial F-statistic.

Question 11

The test statistic used to test the hypothesis of whether a regression coefficient is significantly different from zero, holding all other independent variables constant, is called a(n):

		t-test.
		F-test.
		multicollinearity test.
		autocorrelation test.

Question 12

Regression analysis that analyzes the relationship between one dependent variable and several independent variables is called:

		cluster analysis.
		correlation analysis.
		multiple regression analysis.
		simple regression analysis.

Question 13

The ratio of the regression coefficient to its standard error is called:

		F-statistic.
		t-statistic.
		coefficient of determination.
		partial F-statistic.

Question 14

The coefficient of determination will range between what values?

		-1 and +1
		0 and 1
		-3 and +3
		none of the above

Question 15

The range of values in which we can be confident that the true regression coefficient lies within a given degree of probability is called a:

		confidence interval.
		logistic regression.
		prediction interval.
		none of the above.

Question 16

The estimated regression equation is Y = 10 + 2.5X, if X =0 than the predicted value of Y is equal to

		2.5
		7.5
		12.5
		10

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ECON 010 Chapter Notes - Chapter 12: Simple Linear Regression, Scatter Plot, Regression Analysis

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