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As we stated above, we start factor analysis with principal component analysis, but we quickly diverge as we apply the a priori knowledge we brought to the problem.
This knowledge may be of the form that we "know" how inany factors there should be or it may be more of the nature that allows our experience and intuition about the data guide us as to how many factors there should be. As before, with PCA, we can take the eigenvectors (of unit length) and weight them with the square root of the corresponding eigenvalue:
A real estate agency collected the data shown below, where y = sales price of a house (in thousands of dollars) x 1 = home size (in hundreds of square f
Correlation Analysis Correlation Analysis is performed to measure the degree of association between two variables. The measure is called coefficient of correlation. The coeffic
The Null Hypothesis - H0: The random errors will be normally distributed The Alternative Hypothesis - H1: The random errors are not normally distributed Reject H0: when P-v
The data used is from a statistical software Minitab; London.MPJ is the file that consists of 1519 households drawn from 1980 - 1982 British Family Expenditure Surveys. Data that i
Explain the characteristics of business forecasting.
Consider the following new business venture. An agent is considering investment in one of three real estate parcels: • Option 1: multiunit rentals • Option 2: commercial building
You want to know the thoughts of air travelers in fields such as tickets, comffort, safety, securuty, services and economic growth. You are given a database and 20 questions to ask
Assumptions in Regression To understand the properties underlying the regression line, let us go back to the example of model exam and main exam. Now we can find an estimate o
applications of normal probability distribution
Read the following data on the economy of Angoia and answer/respond to the questions/instructions that follow. Unless otherwise stated, the monetary figures are in real billions o
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