Enteprenureship
ENTREPRENEURSHIP MODULE (ENT 205)
STANDARD DEVIATIONS AND VARIANCES ESTIMATIONS
Estimation of ( and (2
Although there are a number of methods of estimating the standard deviation of a population the sample standard deviation is the most widely used estimator of this parameter. If we use s to make inferences about ( (or s2 to make inference about ( 2 ) the theory on which a confidence interval for ( is based requires that the population sampled has roughly the shape of a normal distribution, in which case the statistic called (2 has as its sampling distribution an important continuous distribution called the chi square distribution [pic] . In the formula as with the t distribution,(n-1) is called degrees of freedom.
(2 Distribution has the following properties
1. It involves squared observations and hence it is always positive. Its value is always greater than or equal to zero.
2. The distribution is not symmetrical. It is skewed to the right so that its skewness is positive. However, as the number of degrees of freedom increases (2 approaches a symmetric distribution. In other words As the degrees of freedom increase, the chi-square curve approaches a normal distribution
3. Similar to t distribution there is a family of (2 distributions. There is a particular distribution for each degree of freedom.
(2 is also called goodness- of fit test. Also used for analyzing qualitative variables such as opinions of persons, religious affiliations, and smoking habits etc. (2 test deals with judgements about proportions of two or more than two populations.
The mean of the distribution is equal to the number of degrees of freedom: μ = v
The variance is equal to two times the number of degrees of freedom: σ2 = 2 * v
When the degrees of freedom are greater than or equal to 2, the maximum value for Y occurs when Χ2 = v – 2.
The chi-square distribution is constructed so that the total area under the curve is equal to 1. The area under the curve between 0 and
STANDARD DEVIATIONS AND VARIANCES ESTIMATIONS
Estimation of ( and (2
Although there are a number of methods of estimating the standard deviation of a population the sample standard deviation is the most widely used estimator of this parameter. If we use s to make inferences about ( (or s2 to make inference about ( 2 ) the theory on which a confidence interval for ( is based requires that the population sampled has roughly the shape of a normal distribution, in which case the statistic called (2 has as its sampling distribution an important continuous distribution called the chi square distribution [pic] . In the formula as with the t distribution,(n-1) is called degrees of freedom.
(2 Distribution has the following properties
1. It involves squared observations and hence it is always positive. Its value is always greater than or equal to zero.
2. The distribution is not symmetrical. It is skewed to the right so that its skewness is positive. However, as the number of degrees of freedom increases (2 approaches a symmetric distribution. In other words As the degrees of freedom increase, the chi-square curve approaches a normal distribution
3. Similar to t distribution there is a family of (2 distributions. There is a particular distribution for each degree of freedom.
(2 is also called goodness- of fit test. Also used for analyzing qualitative variables such as opinions of persons, religious affiliations, and smoking habits etc. (2 test deals with judgements about proportions of two or more than two populations.
The mean of the distribution is equal to the number of degrees of freedom: μ = v
The variance is equal to two times the number of degrees of freedom: σ2 = 2 * v
When the degrees of freedom are greater than or equal to 2, the maximum value for Y occurs when Χ2 = v – 2.
The chi-square distribution is constructed so that the total area under the curve is equal to 1. The area under the curve between 0 and
References: Kinunda-Rutashoba, L and Olomi, D R (eds) (1996), African Entrepreneurship and Small Business Development, Dares Salaam. Lee, J The Motivation of Women Entrepreneurs in Singapore, Women in Management Review Vol.11 No.2. 19996.pp18-29. Osirim, M.J. (1999) African Women 's Entrepreneurship And Cultural Production: The Case of Crocheters and Knitters in Southern Africa, Department of Sociology and Centre for Ethnicities, Communities and Social Policy, Bryn Mawr College. Winn, J Entrepreneurship: Not an Easy Path to Top Management for Women, Women in Management Review Vol.19.Number 3. 2004.pp143153. Woldie, A. and Adersua, A. Female Entrepreneurs in a Transitional Economy: Businesswomen in Nigeria, International Journal of Social Economics, Vol. 31N0.1/2, 2004. Pp.78-93 -----------------------