Select a country from the list. For this country, collect the data on (i) Life expectancy at birth, total (years), (ii) GNI per capita, Atlas method (current US$) and (iii) Improved water source, rural (% of…
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Use a calculator and your sample to calculate ∑X, ∑Y, ∑XY and ∑X2. Use these values to write down the pair of ‘normal equations’ the solutions of which give the constant term (a) and the slope coefficient (b) of the fitted Ordinary Least Squares line Y = a + bX.
Step 2. This step involves taking the partial derivatives and setting them equal zero provides us with candidate points for a minimization or maximization. In this step we write the equation that the partial derivatives will be taken in matrix form.
Step 3. The partial derivatives of the matrix is taken in this step and set equal to zero. b is a vector or coefficients or parameters. Because the equation is in matrix form, there are k partial derivatives (one for each parameter in b) set equal to zero.
Step 4. Simple matrix algebra is used to rearrange the equation. The first order conditions are to set the partials equal to zero. First, all terms are divided by the scalar 2. This removes the scalar from the equation. This is simply for ease. Second, is added to both side of the equation. On the left hand side, the two terms and cancel each other out leaving the null matrix. This step moves to the right hand side.
Step 5. Finally, b is found by pre multiplying both sides by . Division by matrices is not defined, but multiplying by the inverse is a similar operation. Recall, , where I is the identity matrix. Multiplying any matrix, A, by I results in A, similar to multiplying by one in linear algebra.
The coefficient of GDP is 0.0098662. So for every unit increase in GDP, a .0.0098662 unit increase in IN is predicted, holding all other variables constant. On the other hand the p-value associated with the GDP is 0.800 a value greater than 0.05 (significance level), we thus fail to reject the null hypothesis and conclude that the coefficient for GDP (.0098662) is not statistically significantly different from 0. Thus at 5% level of significance
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The patient is a 50 year old female born in 13 March 1961 Kyoto Japan and moved to US 30 years ago. The patient is a mongoloid, is a widow and is a University graduate with a degree in special education.
This method gets the data that can’t be obtained through reports and queries with a high level of effectiveness. This can also be referred to as the computer assistance in digging for and analyzing data and finally analyzing the contents meaning. These tools predict and analyze the future business trends which allow businesses to apply knowledge based decisions.
The process is similar to the extraction of valuable metal hence the term “mining” (Jackson, 2003). Data mining is the process of analyzing extensive data with the aim of establishing correlation between different variables. Consequently, data warehousing is the process of storing data in relational databases that facilitate such queries and analysis.
Data ware housing involves the periodical extraction of data from applications that support business process into a dedicated computer where they are reformatted, validated, summarized and reorganized. The data warehouse therefore
that was seen as relevant to the business and the balance of power between consumer package goods manufacturers like Procter & Gamble, Unilever as well as other big brand names, (Schmarzo, 2013). The period of the availability of information on various aspects such as product
The Maryland College and career- ready only standards are of a varied assortment. This range from career in English language and arts, college careers related to mathematics and mathematical operations, literacy in history and
This means that the evaluation of behavior varies with the location and time and that something may be considered legal in one place but illegal in another locality. Information on crime statistics can be obtained from various sources.
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