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Since this is a mathematical question, we would want to formulate our hypothesis into
mathematical statements.
Since we are dealing with an average in this scenario, the statistical symbol often used to
represent the average plant yield for the entire population of this particular vegetable is the
Greek letter Mu, .
Now, our experimental hypothesis is that pesticides damage the soil, measured by the pounds of
vegetables yielded from these plants. If that is the case, we would expect to see a yield of less
than 30 lbs. of fruit per plant. That is, our hypothesis is that
Since this is the experimental hypothesis, we have no evidence to conclude that this is true. Thus,
we should probably assume that there is no difference between the yields of pesticide-sprayed
and non-sprayed plants. Thus, begin by assuming that:
This second hypothesis is called the null hypothesis, that is, the hypothesis that is assumed until
there is sufficient evidence otherwise. Symbolically, this hypothesis is written and is typically
read as “null hypothesis,” or “h-naught.”
The hypothesis that we believe is called the alternative hypothesis, and is written
, or “h-ay.”
To write these two hypotheses, we would write:
When evidence is insufficient, we say
“Based on sample data, we fail to reject in favor of ”
When evidence is sufficient to conclude that the average is really below 30, we say
“Based on sample evidence, we reject in favor of ”
We are cautious to make these conclusions based on sample data. Certainly, we may have
obtained an oddball sample that doesn‟t represent the population.
Let‟s practice writing some hypotheses. First, off, let‟s make note of the variety of population
characteristics, called population parameters, that we can seek to describe in a study.
Statistics for Decision-Making in Business © Milos Podmanik Page 209