Data Science Study Centre

  Statistics is the branch of mathematics that deals with the collection, analysis, interpretation, presentation, and organization of numerical data. It is a discipline that involves the application of statistical methods and techniques to extract meaning from data and draw conclusions. There are two main types of statistics: descriptive statistics and inferential statistics. Descriptive statistics: Descriptive statistics are used to describe and summarize data. They involve methods of organizing and summarizing data using measures such as central tendency (mean, median, mode), variability (range, standard deviation, variance), and graphical displays (histograms, box plots, scatter plots). Inferential statistics: Inferential statistics are used to make inferences about a population based on a sample of data. They involve methods of hypothesis testing, confidence intervals, and regression analysis to determine the likelihood of a result occurring by chance or to estimate population ...

  Hypothesis tests are statistical procedures used to determine whether an observed effect or relationship between variables is statistically significant or if it could have occurred by chance. The process of hypothesis testing involves the following steps: State the null hypothesis (H0) and the alternative hypothesis (Ha or H1) based on the research question. Choose a level of significance (alpha) to determine the probability of making a type I error (rejecting the null hypothesis when it is actually true). Collect data and compute a test statistic, which measures the degree of difference or relationship between the variables. Determine the p-value, which is the probability of obtaining a test statistic as extreme or more extreme than the observed value, assuming the null hypothesis is true. Compare the p-value with the chosen level of significance. If the p-value is less than the level of significance, reject the null hypothesis and accept the alternative hypothesis. If the p-val...

  In statistics, a hypothesis is a statement that is tested to determine if it is true or not. There are two types of hypotheses: the null hypothesis and the alternative hypothesis. The null hypothesis (H0) is a statement that there is no significant difference between two groups or variables. It is usually a statement of "no effect" or "no relationship" between the variables being studied. The null hypothesis is often the starting point for a statistical analysis, and the goal is to determine whether there is sufficient evidence to reject it. The alternative hypothesis (Ha or H1) is a statement that there is a significant difference or relationship between two groups or variables. It is the opposite of the null hypothesis and is usually what the researcher is trying to prove. The alternative hypothesis is only accepted if there is sufficient evidence to reject the null hypothesis. In short, the null hypothesis is the default assumption that there is no significant ...

  In statistics, a hypothesis is a statement or an assumption about a population parameter or the relationship between two or more variables. It is a tentative explanation for an observed phenomenon that is testable through a statistical analysis. Hypotheses are typically formulated as two opposing statements: the null hypothesis and the alternative hypothesis. The null hypothesis is a statement that assumes no effect or no relationship between the variables under consideration. The alternative hypothesis is the opposite of the null hypothesis and represents the hypothesis of interest or the hypothesis that the researcher wants to prove. For example, suppose a researcher is interested in studying the effect of a new drug on blood pressure. The null hypothesis in this case would be that the drug has no effect on blood pressure, while the alternative hypothesis would be that the drug does have an effect on blood pressure. Once the hypotheses are formulated, statistical tests are used...

  Descriptive statistics is a branch of statistics that deals with summarizing and describing a dataset using numerical measures and graphical displays. The goal of descriptive statistics is to provide a clear and concise summary of the data that can help analysts understand the data and draw insights from it. There are two main types of descriptive statistics: measures of central tendency and measures of variability. Measures of central tendency include the mean, median, and mode. The mean is the sum of all the values in the dataset divided by the number of values. The median is the middle value in the dataset when the values are arranged in order. The mode is the most frequently occurring value in the dataset. Measures of variability include the range, variance, and standard deviation. The range is the difference between the largest and smallest values in the dataset. The variance is the average of the squared differences between each value and the mean of the dataset. The standa...