Speaker 1: For the third chapter, under MBA 202, we will discuss cost estimation and forecasting. So for this chapter's topic outline, we will first introduce what is cost estimation and forecasting, discuss next regression analysis for cost estimation to be followed by forecasting techniques and managerial accounting, and lastly, budgeting and variance analysis. So what is cost estimation? Cost estimation is a formal process that involves determining the monetary value associated with the expenses made during the production of finalized items. Cost estimation helps in fixing the selling price of the final product after achieving appropriate overheads and allowing a certain margin of for profits. The process of cost estimating encompasses the comprehensive evaluation of all financial outlays associated with the design and manufacturing phases, as well as the provision of related service facilities, including machine setup, tool creation, and a percentage of expenses connected to sales, marketing, and administrative functions, commonly referred to as overhead costs. For regression analysis for cost estimation, regression analysis is a prominent method employed in cost estimates to determine the quantities of fixed and variable costs. In order to forecast and strategize for the future, it is typically necessary for managers to decompose mixed expenses into their fixed and variable constituents. Moreover, regression analysis is a statistical technique employed to ascertain the relationship between variables. The study facilitates users' understanding of how the value of a dependent variable changes when one independent variable varies, while another independent variable remains constant. Regression analysis is a statistical methodology utilized to make predictions about future data. There are two main types of regression analysis. We have linear regression and multiple regression. For linear regression, this is a statistical technique used to analyze and model the association between two or more continuous variables. Omega variables are geographically represented on a linear scale. The calculation of linear regression can be performed by utilizing the subsequent formula, which is this formula below, where y is the dependent variable, x is the independent variable, b is the slope of the regression line, a is the intercept of the regression line, and this symbol is our regression residual. For multiple regression, this is a statistical method employed to forecast the value of a dependent variable by utilizing the values of two or more independent variables. After determining the values of each independent variable, they can be employed to estimate the magnitude of influence exerted by the independent variables on the dependent variable. So this is the formula, where y1 is the predicted value of the dependent variable, our b0 is the intercept, followed by the regression coefficients, and these are our independent variables, and lastly, this symbol again is our regression residual. Moving on, we have forecasting techniques and managerial accounting. Forecasting is an accounting methodology that employs empirical data to provide projections of forthcoming patterns. It is vital for any organization, regardless of its stage, whether it is in the first phase of development and formulating a business plan or an established firm. So there are two distincts of forecasting methodologies. We have qualitative forecasting and we have quantitative forecasting. So for qualitative forecasting, this relies on non-quantifiable knowledge. It is particularly crucial in the early stages of a company's establishment as there exists a dearth of historical data. The inclusion of historical data in qualitative forecasting is contingent upon various factors. Next are our different qualitative methods. We have the Delphi method. This methodological framework facilitates the collaboration of specialists in responding to a sequence of questions, wherein the outcomes of the preceding questionnaire dictate the subject matter of the subsequent one. Next is in-house expertise. The responsibility of forecasting is assigned to the staff member or members possessing the highest level of expertise in the relevant subject matter. Individuals utilize their extensive expertise to formulate prognostications. Next is we have our market research. This alternative forecasting approach necessitates substantial investments in terms of time, effort, and resources. Data is gathered through dialogues with current and prospective clientele regarding their specific requirements for particular products or services. Now talking about quantitative forecasting, this is predicted upon the utilization of measurable and manipulable data. The data typically originates from previous time periods. Quantitative forecasting, also known as statistical forecasting, involves the utilization of historical sales or performance data to assess the present trajectory of sales, whether they are on an upward or downward trend, and to determine the extent of business growth or stagnation, as well as the rate at which these changes are occurring. So there are two types of quantitative forecasting. We have time series analysis and we have casual method. For time series analysis, so to obtain a comprehensive understanding of trends, it is necessary to have several years of data pertaining to a particular product or product line while conducting time series analysis. These patterns are indicative of their persistence in the future, or at least this is the underlying premise. For casual method, these strategies include additional variables that impact your business. This advanced technique has the capability to project further into the future compared to time series analysis. The methodology is contingent upon the availability of a substantial dataset encompassing both time series analysis and comprehensive market research. Now talking about budgeting and variance analysis, budgeting and variance analysis are topics that might be perceived as daunting, requiring much effort, and causing confusion among individuals. In practice, these tools serve as valuable instruments in the realm of business, encompassing our conjectures, approximations, and forecasts pertaining to the perspective trajectory of one's enterprise. These are the different or the most common types of variances. We have revenue variations. This arise when the realized revenues deviate from projected revenues. Cost variations. This arise when the actual expenses deviate from the projected expenditures. And lastly, we have volume variations. This arises as a result of disparities in outputs, quantities, or rates of utilization. So that concludes our discussion, and the following are our references. Thank you once again. Thank you for listening.