0
Still curious? Ask our experts.
Chat with our AI personalities
Coach
Rene
Rafa
Add your answer:
Earn +20 pts
What are application of Inferential Statistics in managerial decision making?
census investigation sampling analysis of past trends
Application of inferential statistics in managerial decision making?
cenus investigation sampling analysis of past trends
What is the difference between estimating and guessing?
When you are estimating, you're making an educated "guess". For example, if there's water in a cup, you see that the water is clearly between 300 mL and 310 mL, so an estimation would be anything in between those two values. When you are guessing, you have no foundation to base it on. For example, lets take the water in the cup again. W/o looking at the measurements at all, with no knowledge you make the statement: The cup has about 1000mL of water.
What is the importance of correlation and regression analysis in business decision making?
Correlation and regression analysis can help business to investigate the determinants of key variables such as their sales. Variations in a companies sales are likely to be related to variation in product prices,consumers,incomes,tastes and preference's multiple regression analysis can be used to investigate the nature of this relationship and correlation analysis can be used to test the goodness of fit. Regression can also be used to estimate the trend in a time series to make forecast
Is SPSS used in qualitative data analysis only?
No, SPSS (Statistical Package for the Social Sciences) is not limited to qualitative data analysis only. In fact, SPSS is primarily designed for quantitative data analysis, which involves analyzing numerical data using statistical techniques. It is widely used in fields such as social sciences, psychology, economics, and market research. SPSS provides a range of features and tools for SPSS quantitative data analysis, including: Descriptive statistics: SPSS allows you to calculate and summarize descriptive statistics such as means, standard deviations, frequencies, and percentages. These statistics provide an overview of the distribution and characteristics of your data. Inferential statistics: SPSS offers a variety of statistical tests for making inferences about populations based on sample data. These tests include t-tests, ANOVA (Analysis of Variance), chi-square tests, correlation analysis, regression analysis, and more. Data manipulation: SPSS provides functionalities to manipulate and transform data. You can recode variables, compute new variables, merge datasets, filter cases, and perform various data transformations to prepare your data for analysis. Data visualization: SPSS enables you to create charts, graphs, and plots to visually represent your data. This helps in understanding patterns, relationships, and trends in the data. Advanced statistical techniques: In addition to basic statistical tests, SPSS also supports more advanced techniques. For example, it offers tools for factor analysis, cluster analysis, discriminant analysis, survival analysis, and nonparametric tests.
