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Interpreting Tables

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I need help interpreting these tables. I have started on them but I do no think they are correct. The solutions would be very helpful for my studies.

Problem 1.
Below is a tabulation of the demographic data from the Frequency distribution of a survey done by Ms. Sandra Jones. Her sample consisted of 148 of a total of 3,700 clerical employees in three service organizations.
Based on the tabulation provided below, describe the sample characteristics.
Table 1: Frequency Distributions of Sample (n = 148)
RACE EDUCATION GENDER
Non-whites = 48 (32%) High School = 38 (26%) Males =111(75%)
Whites = 100 (68%) College Degree = 74 (50%) Females = 37 (25%)
Masters Degree = 36 (24%)

AGE # OF YEARS IN ORG. MARITAL STATUS
< 20 = 10(7%) < 1 year = 5 (3%) Single 20 (14%)
20-30 = 20(14%) 1-3 = 25(17%) Married 108 (73%)
31-40 = 30(20%) 4-10 = 98(66%) Divorced 13 (9%)
>40 = 88(59%) >10 = 20(14%) Alternative Lifestyle 7 (4%)

Here is another tabulation of the Means, Standard Deviations, etc., for Ms. Jones' data.
How would you interpret these data?

Table 2 and 3 are in the word doc, refer to the doc.

This is what I came up with but not sure if it's correct.

Table 1 - Description of the sample characteristics
The race of employees based on the sample are majority white at 68% and non-whites at 32%. The education level is that half of the employees have a college education, 24% of the employees have a master degree and 24% of the employees have a high school degree. The majority of the employees are male at 75% and 25% of the employees are female. The majority of the age of employees are greater than 40 years of age at 59%, 7% less than 20 years of age, 14% between 20 - 30 and 20% between 31 - 40 years of age. Most employees (66%) have worked at the organization from 4-10 years, 17% have worked there 1-3 years, 14% have worked there more than 10 years and 3% have worked there less than a year. The marital status where most employees are married at 73%, 14% of employees are single, 9% are divorced and 4% lead an alternative lifestyle.

Table 2 - Interpretation

Table 2 gives you the average (mean) for each of the variables as well as the standard deviation (average spread of sample data about the mean) and the range (minimum to maximum) for the sample data points. This gives you an idea of the employees in the sample, their average age, average number of years married, average stress, job involvement and performance. This tells you if the sample is similar or different employees are from each other. The average age of employees are 37.5 and the average number of years married for employees is 12.1 years. There's a wide variation in the number of years married (standard deviation = 24) indicating ???

Table 3 - Interpretation
In Table B the variables are correlated with each other. This means that you are seeing if they "move together" closely (strong relationship) or loosely (modest relationship) or not at all (no relationship). It shows that there is a strong relationship between age and number of years married and a loose relationship with the other three variables, stress, job involvement and performance.

Age the dependent variable does not have a highly significantly positive correlation to the four independent variables, numbers of years married, stress, job involvement and performance. This makes sense since age is not a factor in job performance.

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Here is another tabulation of the Means, Standard Deviations, etc., for Ms. Jones' data.
How would you interpret these data?
Table 2: Means, Standard Deviations and Other Statistics

VARIABLE MEAN STD. DEV MODE MIN MAX
Age 37.5 18 38 20 64
# of Years Married 12.1 24 15 0 32
Stress 3.7 1.79 3 1 5
Job Involvement 3.9 1.63 4 2 5
Performance 3.6 0.86 3 3 5

From the same research done by Ms. Jones, the following inter-correlation matrix is shown. Interpret these results.
In the age group, there are many people at age of 38. The youngest is 20 and the oldest is 64. Further, all these ages locate within two standard deviations away from the mean. In other ways, there may be no obvious outlier in this data set.
For the number of years married, there ...

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***See attached file for full problem description.***

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