Regression Analysis as a Managerial Research Tool: A Practical Illustration of Demand Analysis in Pakistan
Bibliographic record
Abstract
The study is aimed at analyzing demand estimation and forecasting using regression analysis as a Managerial research tool. The article is about estimating demand of Medicam Toothpaste by viewing the effect of various variables like price of Medicam toothpaste, price of Shield toothbrush, price of Colgate toothpaste, advertisement and total revenue on the demand as well as its forecast for the next quarter. The methodology used is multiple regressions using Ordinary least Square method applied on time series data of 1 st quarter of 2007 to 2 nd quarter of 2014. Coefficients of price of Medicam and price of shield toothbrush show negative association with demand of Medicam toothpaste in Pakistan. The coefficients attached with price of Colgate toothpaste, Advertisement and total revenue of the firm are positively related with demand of Medicam toothpaste. Price elasticity of demand is -0.156, cross price elasticity of demand w. r. t. price of Colgate is 0.014, and w. r. t. price of shield tooth paste is - 0.059, advertisement elasticity of demand is 0.076 and total sales elasticity of demand is 0.0247. The forecast result shows that the demand has increased in the 3 rd quarter of 2014 having demand of 48181.53 units. Keywords: Demand estimation, Demand Forecasting, Elasticities of demand, Regression Analysis, Managerial Research Tools.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".