Statistics And Its Impact On The Quality Of Data

1017 Words Aug 25th, 2014 5 Pages
Statistics is defined as a branch of mathematics used to analyze, explain summarize as well as interpret what we observe- in order to make sense or meaning of our observations. Every day in life we encounter information that originates from diverse forms and ways. This means that to make this information to have sense, there is the need to use statistics. However, due to its focus and empirical on applications, statistics is classically considered a distinctive mathematical science rather than a branch of mathematics (Chance et al, 2005). Thus, some tasks a statistician use are less mathematical; for instance, making sure data collection is carried out in a manner that yields valid conclusions, reporting results, or coding data in ways …show more content…
This means that with inferential statistics, one attempts to reach conclusions, which extend past the immediate data alone. It permits one to use samples to make generalizations concerning the populations from where the samples were drawn. Thus, it is paramount that the sample accurately represents the population under study. These statistics depends on the use of random sampling method that makes sure that a sample is a representative of the entire population under study. A true sample in a given study means that everyone in the population has an equal chance of being chosen for the sample. This statistics take into consideration the sampling error in the sample collected (Kolaczyk, 2009).
Hypothesis is a claim that needs to be justified. In developing a hypothesis, there is need to translate a problem into a statement entailing a statistical measure. The parameter or measure like µ or p is then used in the derivation of a particular hypothesis. For instance, the claim might be that education increases income so µ = average income of the educated. H0 µ ≤ 30000 versus Ha µ > 30000. If the average income of the whole population is known to be about $30,000, now the two competing claims are: H0 (Null hypothesis that says educated earn no better than others) versus Ha (alternative hypothesis, which is one-sided and says that educated earn more.
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