Author: Kanda Data
Calculate Coefficients bo, b1, and R Squared Manually in Simple Linear Regression
Simple linear regression can be used to analyze the effect of one variable on another variable. The regression analysis consists of the dependent variable and the independent variable. Simple linear regression only consists of one dependent variable and one independent variable. If in the regression equation the number of independent variables is two or more than two variables, it is no longer called simple linear regression.
How to Distinguish 0.01, 0.05, and 0.10 Significance Levels in Statistics
A researcher in planning research will develop a hypothesis from the research that will be conducted. The hypothesis is created as a proposition about the population parameters to be tested statistically through samples taken from the population.
How to Select Random Sample using Data Analysis in Excel
The sample is part of the population, including the number and characteristics of the population. In large populations, researchers may not observe all of these populations due to limited funds, labour, and time. Sampling is one solution in research where research results can still represent the characteristics of the observed population.
How to determine the minimum sample size to be representative
Based on the type, research can be divided into survey research and experimental research. In survey research, we generally collect primary data from a population. Researchers can take population data or samples from the population in the study.
How to Calculate Price Elasticity from Linear Regression Equation
Researchers and practitioners often calculate elasticity to see the response of a variable due to changes in other variables. The measure of the degree of response or the degree of sensitivity is called elasticity. The elasticity value is often used to predict changes in demand or supply of an item due to changes in the factors that influence it.
Quantitative data analysis using data analysis toolpak in Excel
Researchers very well know Excel to help research data analysis. So far, excel is mainly used to input data and then present the data in a more informative display. Excel is generally used more for descriptive statistical analysis, creating tables of research results, and creating graphs.
Multiple Linear Regression Analysis for Time Series Data in Excel
The selection of data analysis methods is important in determining the study’s results. Data analysis methods not following statistical theory and scientific principles can potentially cause errors in making research conclusions. The research hypotheses prepared at the beginning of the proposal need to be tested statistically so that the correct findings can be obtained. Therefore, a basic understanding of statistics needs to be understood by those conducting research activities.
The Best Guide for Optimizing Data Analysis in Excel
In addition to understanding the research topic, researchers also need basic data analysis knowledge. Excel is one of the tools often used by researchers to analyze research data. Researchers can use excel for various data analyses. On this occasion, Kanda Data will write the best guide for optimizing data analysis in excel.