Q. ________ is an incredibly powerful tool for analyzing data.

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Q. The square of the correlation coefficient r 2 will always be positive and is called the ________

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Q. Predicting y for a value of x that’s outside the range of values we actually saw for x in the original data is called ___________

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Q. What is predicting y for a value of x that is within the interval of points that we saw in the original data called?

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Q. Analysis of variance in short form is?

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Q. ________ is a simple approach to supervised learning. It assumes that the dependence of Y on X1, X2, . . . Xp is linear.

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Q. Although it may seem overly simplistic, _______ is extremely useful both conceptually and practically.

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Q. When there are more than one independent variables in the model, then the linear model is termed as _______

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Q. The parameter β0 is termed as intercept term and the parameter β1 is termed as slope parameter. These parameters are usually called as _________

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Q. The sum of squares of the difference between the observations and the line in the horizontal direction in the scatter diagram can be minimized to obtain the estimates is generally called?

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Q. ______ regression method is also known as the ordinary least squares estimation.

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Q. __________ refers to a group of techniques for fitting and studying the straight-line relationship between two variables.

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Q. In order to calculate confidence intervals and hypothesis tests, it is assumed that the errors are independent and normally distributed with mean zero and _______

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Q. What do we do the curvilinear relationship in linear regression?

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Q. When hypothesis tests and confidence limits are to be used, the residuals are assumed to follow the __________distribution.

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Q. The IBM _________ analytics appliances combine high-capacity storage for Big Data with a massively-parallel processing platform for high-performance computing.

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Q. ______ is an integrated hosted analytics platform for marketing insights, predictive models, and marketing optimization.

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Q. ________ is rapidly being adopted for computing descriptive and query types of analytics on Big data.

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Q. _________ involves predicting a response with meaningful magnitude, such as quantity sold, stock price, or return on investment.

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Q. Which of the following involves predicting a categorical response?

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