The Historical Context Of Palestine - 1532 Words

As the depiction of certain historical facts serves the sole purpose of justifying the importance of the historical context to the conflict, and not the merit of the events themselves, the following are only a few, yet highly applicable ones to the matter discussed. Briefly going back to ancient history, the region known today as Palestine was first known as Canaan, which derived its name from a people who inhabited it between 3000 - 1500 B.C. They were conquered by a greek people known as Philistines and also Jews, one of the semitic peoples, in the years 1200-1100 B.C. A hundred years later Jews defeated both Philistines and Canaanites, establishing Kingdom of Israel (Smith). This is important, because the first temple in Jerusalem was†¦show more content†¦As Islam expanded rampantly in the years 630-730 A.D., Jerusalem and Palestine were incorporated into Islamic rule, exposing Jews to the Arab rule as well as initiating the clash of religions that thrives to the present day. In A.D. 691, Dome of the Rock, a Muslim temple memorating Muhammad s ascension to heaven was built upon the ruins of the Jewish Temple, thus provoking the latter on the religious grounds, and initiating an ongoing dispute, one of the most prominent in present-day Old City of Jerusalem (Smith). Toward the end of the Ottoman rule (1516-1918) over Palestine, the situation there began to destabilize, most notably following the Ottoman land reform law passed in 1867, which granted foreigners the right to own land if they agreed to pay taxes to the Ottoman government. The aim of the law was to force foreigners to submit to Ottoman jurisdiction in return for their investment in land in the empire. The ruling is essential to the current ethnic plight in Palestine, as it was especially in that region, that those regulations were applicated inconsistently, which opened the way for extensive outside investment and led to numbers of Palestinians acquiring lands, while giving them claim to fight the immigrants of the Zionist Movement (Tessler). The modern Zionism dates back to the second half of the nineteenth century and emerged from the nationalist upheaval as well as anti-Jewish prejudice in both Western and

Karl Marx and Durkheim - 932 Words

The seventeenth and eighteenth centuries were full of evolving social and economic ideas. These views of the social structure of urban society came about through the development of ideas taken from the past revolutions. As the Industrial Revolution progressed through out the world, so did the gap between the class structures. The development of a capitalist society was a very favorable goal for the upper class. By using advanced methods of production introduced by the Industrial Revolution, they were able to earn a substantial surplus by ruling the middle class. Thus, maintaining their present class of life, while the middle class was exploited and degraded. At this time in history, social theorists like Emile Durkheim and Karl Marx†¦show more content†¦Together these comprise the mode of production; Marx observed that within any given society the mode of production changes, and that European societies had progressed from a feudal mode of production to a capitalist mode of p roduction. In general, Marx believed that the means of production change more rapidly than the relations of production (for example, we develop a new technology, such as the Internet, and only later do we develop laws to regulate that technology). For Marx this mismatch between (economic) base and (social) superstructure is a major source of social disruption and conflict. Alienation is a process whereby people come to be divorced or isolated from the society around them Marx argues that alienation in capitalist societies is due to the fact that in work, we each contribute to the common wealth, but can only express this fundamentally social aspect of ourselves through a production system that is not social but privately owned, for which we function as instruments, not as social beings. Criticism Marx attributes alienation to the social organization specific to capitalism. Critics point out that mass society has its own dynamics, which may be distinct fromShow MoreRelatedEmile Durkheim And Karl Marx746 Words   |  3 PagesEmile Durkheim and Karl Marx are considered the founding fathers of sociology. Both men had an influence on the development of sociology. Marx and Durkheim differed in their idea of what alienation consisted of. For Marx, the issue was class conflict. While, for Durkheim, it was a disordered society trying to adapt. Although they both had different concepts of alienation, both men believed that alienation lead to a man’s disconnectedness with society and their natural state of mind. Durkheim and MarxRead MoreEmile Durkheim And Karl Marx Essay1709 Words   |  7 Pages(Bratton Denham, 2014). Two of the main sociological theorists, Karl Marx and Emile Durkheim, had different understandings of the notion about the division of labor. 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Marx, on the other hand, claims that social classes and the conflict betweenRead MoreKarl Marx And Emile Durkheim Essay1976 Words   |  8 Pages Writing in the late 19th and early 20th century, during a drastic period of change, Karl Marx and Emile Durkheim, two of sociology’s most renowned thinkers, challenged multiple facets of the capitalist social structures in which they found themselves. Marx, a conflict theorist, and Durkheim, a functionalist, sought to analyze and explain capitalist society. In this brief analysis, their theories regarding the will be compared, contrasted, and critically engaged with - highlighting the differencesRead MoreKarl Marx And Emile Durkheim1316 Words   |  6 Pagessurvive. However, all of that had changed when Capitalism and industrialization have been introduced to the world. Karl Marx and Emile Durkheim had different views on what the important aspects are that made up â€Å"modern† society. To Marx, the conflict between the classes and the division of labour caused social structures, which, as a result, caused alienation, which, according to Marx, are important aspects of modern society. With Capitalism c ame along industrialization, which required workers andRead MoreEmile Durkheim vs. Karl Marx1689 Words   |  7 Pages------------------------------------------------- ------------------------------------------------- Emile Durkheim vs. Karl Marx Durkheim vs. Marx Introduction: For so many years, authorities from each field have deliberated normative theories to explain what holds the society together. Almost each specialist, from structural functionalism, positivism and conflict theory perspective, had contributed their works trying to illustrate main problematic to our society. In one way, one of the EmileRead MoreThe Views of Marx Weber, Karl Marx and Emile Durkheim on Religion 1475 Words   |  6 PagesMarx Weber, Karl Marx and Emile Durkheim Ordinarily, religion is one of the rationales of social orientations, that in one way or another influences the society’s social stability. This is because religion is the impelling force for regulations in the society as well as a destabilizing drive for transformation. Marx Weber together with Karl Marx and Emile Durkheim were very influential personalities in the course of the 19th century, and even now. In one way or another, these persons attempted toRead MoreKarl Marx, Max Weber And Emile Durkheim1447 Words   |  6 Pageswill be a part of culture and society. Karl Marx, Max Weber, and Emile Durkheim are the top three most important figures in sociology; and although each of them viewed religion differently, I strongly believe that they understood its power, and demonstrated its importance to people and societies. As such, I will utilize all three of these great minds, to demonstrate religion as an important and permanent part of culture and society. Let s begin with Karl Marx, and his conflict theory. AccordingRead MoreEssay on Perspectives of Emile Durkheim and Karl Marx1215 Words   |  5 PagesPerspectives of Emile Durkheim and Karl Marx The seventeenth and eighteenth centuries were full of evolving social and economic ideas. These views of the social structure of urban society came about through the development of ideas taken from the past revolutions. As the Industrial Revolution progressed through out the world, so did the gap between the class structures. The development of a capitalist society was a very favorable goal for the upper class. By using advanced methods of productionRead MoreKarl Marx, Emile Durkheim And Max Weber929 Words   |  4 Pagespeople did not have in the past such as getting food from the grocery store instead of having to find food on our own. 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The Importance of Authenticity in a Man’s Life Free Essays

Authenticity, as defined by existentialist philosophers, is the degree to which one is true to one’s own personality, spirit, or character, despite external pressures. According to Jean-Paul Sartre, â€Å"Existence precedes essence†, in other words, man makes himself. In order for him to define himself, he should be totally free. We will write a custom essay sample on The Importance of Authenticity in a Man’s Life or any similar topic only for you Order Now But, how can he be free totally? Man can be totally free when he lives an authentic way of living. By living a life of authenticity, man should not seek guidance towards the established codes of life. He should decline every sort of objective morals and values that is set by his society for him?. By this, he should be living his life according to his true self. Living by his true nature requires him his freedom of choice. And by creating his own choices, he freely makes his own actions despite external forces. These actions which he freely chooses are now the basis of his existence. But in order for him to be able to live an authentic life, he must take full responsibility for all of his actions. Knowing things about freedom and authentic living, what are its implications to man’s life? Being authentic will enable a man to live his life to the fullest. And living life to the fullest means is to have a life that is joyful, meaningful, and full of values and happiness. By living authentically, he will be able to liberate himself from the barriers that are cast to him by his society. By transcending the presupposed purposes-in-life, the true purpose of his existence become so clear to him. With the knowledge of his existence’s ultimate purpose, he can formulate the best decisions for himself. Deciding according to his own choices will lead him towards the fulfilment of his personal goals. In sum, all these things will guide him to a more comfortable and a better life in which he lives through the assistance of his own choices and according to his very true nature. Indeed, authenticity is truly significant to a man’s life. The most mportant aspect of living an authentic life is total freedom. Because of total freedom, man is able to make personal choices and also, he leads his life to anew. He is no longer having problems when it comes to decision making for the reason that he already has a clear view of his ultimate purpose. For one to acknowledge his freedom of choice and the responsibility that he hold as a being is, according to Sartre, to have an authentic way of living. How to cite The Importance of Authenticity in a Man’s Life, Papers

Report On Quantitative Techniques In Business

Question - Prepare a report on Quantitative Techniques in Business? Answer - Introduction Quantitative analysis is a basic part of each and every business or industry. In each business and industry, there is a huge amount of data produced and therefore management team of such businesses or industries needs to analyze these data sets for the planning and marketing. Quantitative analysis also called as statistical analysis and it is consist of descriptive statistical measures as well as some inferential measures. Statistical analysis plays an important role in the planning and other functions of managerial team of the business or company or industry. Here, we have to study of quantitative techniques in business for one particular case. We are given a data for sunglasses for 12 months for the variables sales, prices, advertising expenditure, number of households, average sales experience and mean daily hours. The detailed table including the data is given in the appendix. Also, units for each variable are explained detail in the table attached in the appendix. We have to ana lyze this data by using some statistical methods. We have to see some descriptive statistics for the each variable under study. Also we have to see some graphical analysis for the given variables. From these graphs, we have to check whether there is any linear relationship or association observed between the two variables or not. For more detail of the linear relationship or association between the different variables under study, we have to see the correlation analysis. For this purpose, we have to see the correlation matrix which shows the relationship between every two variables. From this correlation analysis, we can check whether the linear relationship is significant or not. Also, we have to see the regression model for the given variables. Regression model helps for further estimation. Regression analysis explains the detailed relationship between and among the variables under study. Let us see all this quantitative or statistical analysis step by step given below. Descriptive Statistics-Graphical Analysis In this part, we have to see the descriptive statistics and graphical analysis for the given variables. First we have to see some descriptive statistics for the given variables such as sales of the sunglasses, price, advertising expenditure, number of households, average sales experience and mean daily hours. Descriptive statistics consist of the mean, mode, median, standard deviation, variance, minimum, maximum, kurtosis, skewness, etc. For the analysis of given variables, we have to use the SPSS software for analysis purpose. The descriptive statistics for the given variables are given in the following tables. Descriptive Statistics N Minimum Sum Mean Std. Deviation Variance Sales 12 75.00 2273.00 189.4167 83.25804 6931.902 Price 12 2.10 49.50 4.1250 1.60631 2.580 Advert_exp 12 2.00 177.00 14.7500 10.48050 109.841 No._households 12 500.00 7456.00 621.3333 102.51061 10508.424 Avg.Sales.experience 12 10.00 177.00 14.7500 2.95804 8.750 Mean_daily_hours 12 2.00 77.80 6.4833 3.16998 10.049 Valid N (listwise) 12 The average sales for the sunglasses is given as 189.4167(000). The standard deviation for sales for the sunglasses is given as 83.25804(000). All averages and standard deviations are summaries in the above table. Some other descriptive statistics are given in the following table: Descriptive Statistics N Range Maximum Mean Skewness Kurtosis Statistic Statistic Statistic Std. Error Statistic Std. Error Statistic Std. Error Sales 12 243.00 318.00 24.03453 -.061 .637 -1.368 1.232 Price 12 4.70 6.80 .46370 .626 .637 -1.095 1.232 Advert_exp 12 28.00 30.00 3.02546 .136 .637 -1.768 1.232 No._households 12 270.00 770.00 29.59226 .264 .637 -1.787 1.232 Avg.Sales.experience 12 8.00 18.00 .85391 -.163 .637 -1.468 1.232 Mean_daily_hours 12 9.50 11.50 .91510 .076 .637 -1.232 1.232 Valid N (listwise) 12 For the variables sales of sunglasses and average sales experience, the skewness values are negative, this implies that the distribution is skewed at left side for these two variables. For all other variables, the distribution is positively skewed. All kurtosis values are negative for all variables. Now, we have to see some graphical analysis for the given variables. By using these graphs, we have to check the linear relationship or association between the two variables. For this purpose, we have to use the scatter diagram. Scatter diagram explains the relationship between the two variables graphically. The scatter diagram for the price and sales of sunglasses is given below: This diagram shows that there is negative association between the two variables sales and price. This scatter plots shows the approximately linear relationship exists between the sales and price. This scatter diagram implies that as the price of the sunglasses increases, the sales of the sunglasses decreases. Now, let us see the scatter diagram for the variable sales and advertisement expenditure. The diagram is given below: This scatter diagram also shows an approximately linear relationship or correlation between the sales and advertisement expenditure. This scatter shows positive linear relationship exists between the two variables sales and advertisement expenditure of sunglasses. This means that as the advertisement expenditure increases, the sales of the sunglasses also increases. Now, let us see the scatter diagram for the variable sales and average sales experience for sunglasses. The scatter diagram is given below: This diagram do not implies any linear relationship or association between the two variables sales of sunglasses and average sales experience for the sunglasses. This implies that the sales of the sunglasses do not depend upon the average sales experience for the sunglasses. Now, let us see the scatter diagram for the variable sales and number of households for sunglasses. The scatter diagram is given below: This scatter diagram implies an approximately linear relationship or association exists between the two variables sales of sunglasses and number of household in the area. This scatter diagram represents approximately positive relationship. This means that as the number of households increases, the sales of the sunglasses also increases. Now, let us see the scatter diagram for the variable sales and mean daily hours of sales for sunglasses. The scatter diagram is given below: This scatter diagram implies a positive linear relationship exists between the two variables mean daily hours and sales of the sunglasses. This means that as the mean daily hours increases, the sales of the sunglasses also increases. Correlation Analysis In the above part, we see the relationship between the two different variables by using the scatter diagram. In this part, we have to find the correlation coefficient between these two different variables under study. Correlation coefficient gives the exact extent of the linear relationship or association between these two variables. For this purpose, we have to find the correlation coefficient between the variables. The SPSS output for the correlation coefficients is given below: Correlations Sales Price Advert_exp No._households Avg.Sales.experience Mean_daily_hours Sales Pearson Correlation 1 -.922** .964** .641* .049 .973** Sig. (2-tailed) .000 .000 .025 .880 .000 N 12 12 12 12 12 12 Price Pearson Correlation -.922** 1 -.885** -.601* .030 -.851** Sig. (2-tailed) .000 .000 .039 .926 .000 N 12 12 12 12 12 12 Advert_exp Pearson Correlation .964** -.885** 1 .595* .130 .923** Sig. (2-tailed) .000 .000 .041 .688 .000 N 12 12 12 12 12 12 No._households Pearson Correlation .641* -.601* .595* 1 -.272 .586* Sig. (2-tailed) .025 .039 .041 .393 .045 N 12 12 12 12 12 12 Avg.Sales.experience Pearson Correlation .049 .030 .130 -.272 1 .015 Sig. (2-tailed) .880 .926 .688 .393 .963 N 12 12 12 12 12 12 Mean_daily_hours Pearson Correlation .973** -.851** .923** .586* .015 1 Sig. (2-tailed) .000 .000 .000 .045 .963 N 12 12 12 12 12 12 **. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed). From the above table, the correlation between the two variables sales and price is given as -0.922, and this is high negative relationship. This fact we already observed in the scatter diagram. This correlation coefficient implies that as the price of the sunglasses increases, the sale of the sunglasses decreases and vice-versa. The correlation coefficient between the sales of the sunglasses and advertisement expenditure for the sunglasses is given as 0.964, this implies that there is high positive correlation between the sales of the sunglasses and advertisement expenditure for the sunglasses. This means that if we increase the budget for the advertisement for the sunglasses, it results into the increment of the sales of the sunglasses. The correlation coefficient between the sales of the sunglasses and average sales experience is given as 0.049, this is very low positive correlation coefficient. This implies that there is very low or no any correlation or linear relationship or ass ociation exists between the two variables sales of the sunglasses and the average sales experience. This represents that there is no important role for the experience of sales of sunglasses for increasing the total sales for the sunglasses. The correlation coefficient between the sales of the sunglasses and the mean daily hours is given as 0.973 and this is very high positive correlation coefficient. This means that there is strong correlation or linear relationship exists between the two variables sales of the sunglasses and the mean daily hours of sales of sunglasses. If the mean daily hour of sales increases, it results in the total increment of the sales of the sunglasses. Regression Analysis In quantitative techniques or statistical analysis, the regression analysis is nothing but the statistical process for the estimating the relationships among the different variables under study. This regression analysis technique includes the formation of regression equation for the estimation purpose. In this technique, we focus on one dependent variable and one or many other independent variables. In the regression analysis, the dependent variable is assumed as the linear function of the one or more than one independent variables. Now, we have to see the regression model for the linear relationship between all these variables. We consider the sales of the sunglasses as the dependent variable and for this regression model, we consider the independent variables as the price of the sunglasses, advertisement expenditure for the sunglasses, number of households in the area, average sales experience and mean daily hours for the sunglasses. The statistical analysis for this regression mod el for the given variables under study is very important for the future planning for sales of the sunglasses. This model or regression equation will help in planning and management and it will helpful for the estimation purpose. The SPSS output for this regression model is given below: Descriptive Statistics Mean Std. Deviation N Sales 189.4167 83.25804 12 Price 4.1250 1.60631 12 Advert_exp 14.7500 10.48050 12 No._households 621.3333 102.51061 12 Avg.Sales.experience 14.7500 2.95804 12 Mean_daily_hours 6.4833 3.16998 12 Correlations Sales Price Advert_exp No._households Avg.Sales.experience Mean_daily_hours Pearson Correlation Sales 1.000 -.922 .964 .641 .049 .973 Price -.922 1.000 -.885 -.601 .030 -.851 Advert_exp .964 -.885 1.000 .595 .130 .923 No._households .641 -.601 .595 1.000 -.272 .586 Avg.Sales.experience .049 .030 .130 -.272 1.000 .015 Mean_daily_hours .973 -.851 .923 .586 .015 1.000 Sig. (1-tailed) Sales .000 .000 .012 .440 .000 Price .000 .000 .019 .463 .000 Advert_exp .000 .000 .021 .344 .000 No._households .012 .019 .021 .196 .023 Avg.Sales.experience .440 .463 .344 .196 .482 Mean_daily_hours .000 .000 .000 .023 .482 N Sales 12 12 12 12 12 12 Price 12 12 12 12 12 12 Advert_exp 12 12 12 12 12 12 No._households 12 12 12 12 12 12 Avg.Sales.experience 12 12 12 12 12 12 Mean_daily_hours 12 12 12 12 12 12 Variables Entered/Removeda Model Variables Entered Variables Removed Method 1 Mean_daily_hours, Avg.Sales.experience, No._households, Price, Advert_expb . Enter a. Dependent Variable: Sales b. All requested variables entered The model summary for this regression model is given below: Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .995a .990 .982 11.07901 a. Predictors: (Constant), Mean_daily_hours, Avg.Sales.experience, No._households, Price, Advert_exp For this regression model, the multiple correlation coefficient R is given as 0.995 and this implies that there is high linear relationship exists between the dependent variable sales of the sunglasses and other independent variables such as price, advertisement experience, number of households, average sales experience and mean daily hours for the sale of sunglasses. The value of coefficient of determination or R square is given as 0.990, this implies that about 99% of the variation in the dependent variable sales of the sunglasses is explained by the independent variables price, advertisement expenditure, number of households, average sales experience and mean daily hours for the sale of sunglasses. In every regression model, ANOVA is very important for taking decision about the regression model. The ANOVA table is given as below: ANOVAa Model Sum of Squares df Mean Square F Sig. 1 Regression 75514.449 5 15102.890 123.043 .000b Residual 736.467 6 122.745 Total 76250.917 11 a Dependent Variable: Sales. b. Predictors: (Constant), Mean_daily_hours, Avg.Sales.experience, No._households, Price, Advert_exp For this ANOVA table, we get the test statistic value F as 123.043 and the p-value is given as the 0.000. So, here, p-value is less than the level of significance or alpha value 0.05 or 0.01, so we reject the null hypothesis that the given regression model is significant. The coefficients for the regression equation or model are given in the following table: Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. 95.0% Confidence Interval for B B Std. Error Beta Lower Bound Upper Bound 1 (Constant) 76.051 46.882 1.622 .156 -38.667 190.768 Price -12.114 4.742 -.234 -2.555 .043 -23.718 -.511 Advert_exp 1.916 1.061 .241 1.806 .121 -.680 4.513 No._households .054 .045 .066 1.189 .279 -.057 .164 Avg.Sales.experience .981 1.342 .035 .731 .492 -2.302 4.265 Mean_daily_hours 13.449 2.864 .512 4.696 .003 6.442 20.457 a. Dependent Variable: Sales The regression equation for this regression model under study is given as below: Sales = 76.051 12.114*Price + 1.916*advertisement expenditure + 0.054*number of households + 0.981*average sales experience + 13.449*mean daily hours. Conclusion and recommendation (s) The correlation between the two variables sales and price is given as -0.922, and this is high negative relationship. This correlation coefficient implies that as the price of the sunglasses increases, the sale of the sunglasses decreases and vice-versa. So, it is recommended that do not increase the price of the sunglasses in high extent. The correlation coefficient between the sales of the sunglasses and advertisement expenditure for the sunglasses is given as 0.964, this implies that there is high positive correlation between the sales of the sunglasses and advertisement expenditure for the sunglasses. This means that if we increase the budget for the advertisement for the sunglasses, it results into the increment of the sales of the sunglasses. So, it is recommended that increase the budget for the advertisement of the sunglasses. The correlation coefficient between the sales of the sunglasses and average sales experience is given as 0.049, this is very low positive correlation coefficient. This implies that there is very low or no any correlation or linear relationship or association exists between the two variables sales of the sunglasses and the average sales experience. This represents that there is no important role for the experience of sales of sunglasses for increasing the total sales for the sunglasses. So, it is recommended that do not give importance for the experience of the employee for the sale of the sunglasses. The correlation coefficient between the sales of the sunglasses and the mean daily hours is given as 0.973 and this is very high positive correlation coefficient. This means that there is strong correlation or linear relationship exists between the two variables sales of the sunglasses and the mean daily hours of sales of sunglasses. If the mean daily hour of sales increases, it results in the total increment of the sales of the sunglasses. So, it is recommended that increase the total hours of sales. The multiple correlation coefficient R for given regression model is given as 0.995 and this implies that there is high linear relationship exists between the dependent variable sales of the sunglasses and other independent variables such as price, advertisement experience, number of households, average sales experience and mean daily hours for the sale of sunglasses. The value of coefficient of determination or R square is given as 0.990, this implies that about 99% of the variation in the dependent variable sales of the sunglasses is explained by the independent variables price, advertisement expenditure, number of households; average sales experience and mean daily hours for the sale of sunglasses. References Curwin J. and Slater R. (2007) Quantitative Methods for Business Decisions, (5thedn) Chapman Hall Wisniewski, M (2010) Quantitative Methods for Decision Makers, (5th edn) FT Prentice Hall Lucey T (2002) Quantitative Techniques, Thomson Learning Oakshott L (2006),Essential Quantitative Methods for Business, Management and Finance,(3ndedn) Palgrave Macmillan Swift, L, Piff, S. (2010) Quantitative Methods for Business, Management and Finance, (3rd end) Palgrave Field, A. (2009). Discovering statistics using SPSS. Sage publications. Sekaran, U. (2006). Research methods for business: A skill building approach. John Wiley Sons. Cochran, William G.; Cox, Gertrude M. (1992). Experimental designs (2nd Ed.), New York: Wiley. Lehmann, E.L. (1959) Testing Statistical Hypotheses. John Wiley Sons. Montgomery, Douglas C. (2001). Design and Analysis of Experiments (5th Ed.), New York: Wiley. Appendix The table for the data is given below: Months Sales (000) Price () Advert Exp (000) No. Households Av. Sales Experience (years) Mean Daily Hours (number) (Number) January 75 6.8 2 515 10 2.4 February 90 6.5 5 542 18 4 March 148 6 6 576 18 5.2 April 183 3.5 7 617 11 6.8 May 242 3 22 683 14 8 June 263 2.9 25 707 18 8.4 July 278 2.6 28 500 17 10.4 August 318 2.1 30 742 14 11.5 September 256 3.1 22 747 12 9.6 October 200 3.6 18 770 13 6.1 November 140 4.2 10 515 18 3.4 December 80 5.2 2 542 14 2 The measurements and units for the variables under study are given in the following table: Variable Measurement Sales Total sales for the month (000) Price Average price of a sun glasses for the month () Advertising Exp. Average monthly expenditure incurred on advertising (000) Households The number of people in the community for the period month Experience Average number of years of sales experience (years) Hours of Sunshine Mean daily hours of sunshine (Hours)