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Business Statistics and Interpretation of the Dataset

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    This section presents the findings and interpretation of the dataset. The data has been prepared, explored, analyze, represented and validated on issues relating to business statistics. Now that the dataset is quantitative in nature, it has been analyzed using both descriptive and inferential statistics. The descriptive statistics were used to describe and summarize the data in the form of frequencies, percentages, and means. The inferential statistics, on the other hand, were used to help make inferences and draw conclusions. Statistical test including variances, standard deviations, paired-t-tests, spearman correlation were also used to test the hypothesized statements. All tests of significance were computed at α = 0.05. Given that this is a business statistic, setting alpha at 0.05 and a confidence level at 95% is ideal since it gives the best assumption should the results be statistically significant.

    Data is very important in decision making, especially in business and managerial decision making. For instance, before deciding on a business, the managers should have the relevant evidence which is obtained from the right sources. Reading and interpreting statistical information in a business should be the basis of a decision-making process. For example, determining the age categories of the populations is important because it will show the active population who are still fit for the employment opportunities, thus helping in making effective decisions.

    The results have been sub-divided into sections and subsections. The information of the respondents such as wife’s hours of work in 1975, number of children less than 6 years old in household, number of children between 6 and 18 years of age, wife’s age in years, wife’s educational attainment, in years, wife’s hourly wage, in 1975 dollars, husband’s hours worked in 1975, husband’s age in years, husband’s educational attainment, in years, family income, in 1975 dollars, live in a large city, actual years of wife’s previous labor market experience and Women wage level has been presented first by use of descriptive statistics. After the descriptive statistics of the data have been discussed, the inferential statistics have been presented based on the hypothesized statements. Microsoft suite Excel was used to analyze the data.

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