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When enough experimental results confirm a hypothesis, a well-tested explanation known as a theory is developed. The theory is further subjected to more well-designed experiments and if there is continued regularity in results, scientists may accept the theory as a law (Shipman, Wilson, and Todd).
The data below could be subjected to different analyses in physical sciences and statistical science.
Average temperature recorded (0C)
January: 32
February: 30
March 25
April: 26
May: 25
June: 24
July: 18
August: 22
September: 24
October: 25
November: 24
December: 27
Hypothesis: Temperatures are highest during December, January, and February because the sun is overhead the Tropic of Capricorn.
In physical science, further experiments would then be conducted, and studies carried out to prove right or wrong the hypothesis.
Statistical science explores the relationships between different variables to establish the nature of the relationship between various aspects of nature. Statistical science requires that once data is collected, it becomes organized in a way that will enable others to experience the data which has been collected. For this purpose, it makes use of specific models and tools such as graphs and charts. Statistical Science, thus, evaluates and interprets confidence intervals and significance tests (Diggle and Chetwynd).
The same data, in statistical science, can be organized as below:
Average temperature (0C)
Jan, Feb, Mar: 29
Apr, May, Jun: 25
Jul, Aug, Sep: 21.3
Oct, Nov, Dec: 25.3
Average Temperature throughout the year = 25.2 0C
Physical sciences use the scientific method of study to prove or disprove a theorem whereas statistical science is based on quantitative variables which are subjected to mathematical theorem for analysis (Vaughan).
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