A1. There are two types of statistics that are often referred to when making a statistical decision or working on a statistical problem. Descriptive statistics utilize numerical and graphical methods to look for patterns in data set, to summarize the information revealed in a data set and to present information in a convenient form that individuals can use to make decisions (Singpurwalla, 2013).Descriptive statistics main goal is to describe a data set, hence the class of descriptive statistics include both numerical measures and graphical displays of data.
Inferential statistics utilizes sample data to make estimates, decisions, predictions, or other generalizations about a larger set of data (Singpurwalla, 2013).The main goal of inferential statistics is to make a conclusion about a population based off a sample of data from the population.
A2. The population is the whole set of values, or individuals, that the information collector is interested in. The sample is a subset of the population, and is the set of values that are actually use in estimation. For example, if a person wants to know the average height of the residents of India, that will be the population, i.e., the population of India. As India population is quite large a number, and we wouldn't be able to get data for everyone there. So the collector draw a sample, to get some observations, or the height of some of the people in India (a subset of the population, the sample) and do the inference based on that.
A3.
A) The weight of watermelon: It is a continuous variable. The weight of a watermelon is continuous because it can be measured in fraction of units. If the watermelon weighs in between 1 and 2 pounds, we can be more accurate and say it weighs 1.6 pounds, or 1.68 pounds, or even 1.6822398472958 pounds. We don't have to round it. We might choose to, but we don't have to.
