You can test a hypothesis with very little information. For hypothesis testing you will have a null hypothesis, and alternative and some test statistic. The hypothesis test consists of checking whether or not the test statistic lies in the critical region. If it does, then you reject the null hypothesis and accept the alternative. The default option is to stick with the null hypothesis.
If the number of observations is very small then the critical region is so small that you have virtually no chance of rejecting the null: you will default to accepting it.
Different test have different powers and these depend on the underlying distribution of the variable being tested as well as the sample size.
There are two types of statistics. One is called descriptive statistics and the other is inferential statistics. Descriptive statistics is when you use numbers. Inferential statistics is when you draw conclusions or make predictions.
That, very often, it depends who is paying for the statistics to be drawn up.
Statistics is used to design the experiment (what type of data needs to be obtained and how much), then statistics is used to analyze the data (make inferences and draw conclusions).
1)Ask a question 2)Make a hypothesis (predict what will happen with your experiment) 3)Research your hypothesis 4)Test your hypothesis 5)Collect/organized your data 6)Results 7)Draw a conclusion
There are both advantages and disadvantages of data collection methods in statistics. The main advantages are the metrics and correlation one can draw from statistics. The disadvantages stem from sampling errors.
There is no inferential data. There is inferential statistics which from samples, you infer or draw a conclusion about the population. Hypothesis testing is an example of inferential statistics.
One can draw a tentative hypothesis by clearly examining the varriables from the literature.
If the conclusion you draw from the data supports your hypothesis.
1). identify the problem 2). collect information 3). make a hypothesis 4). test your hypothesis 5). record and analyze 6). draw a conclusion
That its wrong (false).
There are two types of statistics. One is called descriptive statistics and the other is inferential statistics. Descriptive statistics is when you use numbers. Inferential statistics is when you draw conclusions or make predictions.
That, very often, it depends who is paying for the statistics to be drawn up.
In order to form a hypothesis, you draw on everything you know and everything that you can imagine. It's a creative process.
draw conclusions
draw conclusions
draw conclusions
draw conclusions