Introduction To ART Essay Example | Topics and Well Written Essays - 500 words

Introduction To ART - Essay Example The shapes of these rings are quite different. The first ring from the left is round with a square diamond decoration that is yellow in color. The second ring is beige in color and is round in shape but it is flat from the front view. The other ring is blue in color and it is also thickly rounded with its surface also decorated with different lines. The lines that repeat themselves in the background develop unity as they show how different colors such as blue, purple and shades of yellow could be used together. Generally, the outline of this advertisement entails warm colors of different tones. The colors have at least two tones; dark and light. All in all, the different colors used on the rings could be said to be gender specific. Thick and thin lines have been used in this advertisement. The thick dark lines show the dark tone of the colors used and the thin lines have been used to indicate the light shades of the colors used. The rings have been symmetrically represented at the bottom of the advertisement unlike the upper part that has the statement. The texture of the background surface has been depicted as rough by the bold checked lines at the top while the bottom has faint checked lines that depict some smoothness. The advertisement was placed online by the Rocks by Request Company to reach the several masses that have access to the internet so that they could learn about the qualities of diamond before they can buy them form potential jewelers. The retailers also used internet advertisement so as to increase their sales. The company has maintained connectivity so as to include human characteristics in e-commerce by including both technology and culture in organizations that retail in diamonds. Rings have always been a symbol of love in the form of material. Therefore, diamond rings would symbolize uniqueness and status of the couple as not many people are able to buy them. The different colors used on

Dynamic Regression A Simulation Exercise Math Problem

Dynamic Regression A Simulation Exercise - Math Problem Example From the chart it is also the drop is also evident in the market and MOTOR returns and this shows that a drop in the market returns will also signify a drop in the returns of the stocks in the market. Finally from the chart it is evident that there was a decline in the market returns in 1987 showing that returns for the other stocks also declined. We use 120 0bservations to estimate the model estimate the model rjt = j + jrmt + Ujt for both stocks, we use MOTOR return data for the year 1976 to 1985, after estimation sung the TSM software the results show that rjt = 0.00255 + 0.7193 rmt the above model means that is we hold all factors constant and the market return level is equal to zero then the MOTOR stock return will be 0.00255, also if we hold all factors constant and we increase the market return level by one unit then the MOTOR stock return level will increase by 0.7193 units. ... The above model means that is we hold all factors constant and the market return level is equal to zero then the GPU stock return will be 0.00063, also if we hold all factors constant and we increase the market return level by one unit then the GPU stock return level will increase by 0.4297 units. The R squared for this model is 0.0854and this means that 8.54% of deviations in the dependent variable are explained by the independent variable. The correlation of determination R squared value for this model depicts a weak relationship between the explanatory variable and the dependent variable. Hypothesis testing: We test hypothesis for the estimated coefficients in the two models, MOTOR model: rjt = 0.00255 + 0.7193 rmt MOTOR model Constant: Null hypothesis: = 0 Alternative hypothesis 0 Standard error: 0.00737 Coefficient: 0.00255 T calculated = 0.00255 / 0.00737 = 0.34599 T critical at 95% level of test = 1.95996 When the T calculated value is less than the T critical value we accept the null hypothesis, in the above case therefore we accept the null hypothesis that = 0 and therefore the constant is not statistically significant at 95% level of test. Motor Model Slope: Null hypothesis: = 1 Alternative hypothesis: 1 Standard error: 0.12481 Coefficient: 0.7193 T calculated = 1- 0.7193/ 0.12481= 2.249 T critical at 95% level of test = 1.95996 When the T calculated value is greater than the T critical value we reject the null hypothesis, in the above case therefore we reject the null hypothesis that = 0 and therefore the constant is statistically significant at 95% level of test. GPU model: rjt = 0.00063 + 0.4297 rmt GPU model Constant: Null hypothesis: = 0 Alternative hypothesis 0 Standard error: 0.00841 Coefficient: 0.00063