1. One - way ANOVA is used to
compare the means of multiple
poulations or processes using a
single comparison factor, such as
geographic location or
comparison of water quality from
different river systems.
2. In many situations, we need to
examine the differences among
than two groups.
3. The groups involved can be
classified according to levels of a
factor of interest.
1. Sampling error would indicate
that the standard error provides
an evaluating of the likely error
associated with a particular
estimate.
2. This interval is called an interval
estimate [or confidence interval]
where the interval is centred at the
point estimate for the population
mean.
3. From our knowledge of the normal
distributions we know that 95% of
the distribution lies within + - 1.96
standard deviations of the mean.
1. Data is classified into 2 general
categories : attributes & variables.
When using attribute data, the
focus is on learning about 1 or
more specific non-numerical
characteristics of the population
being sampled. Examples of
attributes are : red/green, yes/no,
small/medium/large.
2. Confidence is the probability that
the actual population value being
estimated will be contained
within the precision interval of
our estimate.
3. The precision interval represents
the total amount of sampling
error that you should expect for
any specific sample size.
4. Three factors to determine the
sample size :
(A) the desired confidence level,
which determines the value of
Z, critical value of the
standardize normal
distributions.
(B) the acceptable sampling error
(C) the standard deviation
- the variance & standard deviation provide a measure of how dispersed the data values (x) are about the mean value (x^).
- because of its close links with the mean, the standard deviation can be greatly affected if the mean gives a poor measure of central tendency.
- the coefficiet of variation represents the ratio of the standard deviation to the mean, & it is a useful statistic for comparing the degree of variation from one data series to another.
- standard deviations vary according to the size of values in the distribution and may not even be in the same unit of measurement.
- for example, if the coefficient of variation is 10% then this mean that the standard deviation is equal to 10% of the average.
- for some measures, the standard deviation changes as the average changes.
- in this case, the coefficient of variation is the way to summarize the variation.
- a box plot is a way of summarizing a set data measured on an interval scale. It is often used in exploratory data analysis. It is a type of graph which is used to show the shape of the distribution, its central value & spread. The picture produced consists of the most extreme values in the data set [max & min ], the lower & upper quartiles & the median.
- box plots are very useful when large numbers of observations are involved & when two/more data sets are being compared. They are helpful for indicating whether distribution is skewed & whether there are any unusual observations [outliers] in the data set.
- simple random sampling
- stratified random sampling
- cluster sampling
- multistage sampling
- systematic random sampling
(A) Mean : if the mean is calculated from the entire population of the data set then the mean is called population mean.
(B) Median : as the middle number when the data is arranged in order of size.
(C) Mode : the number which occurs most frequently [the most popular number].
(D) Variability : is a measure of how much data value differs from one another or equivalent, how widely the data values are spread out around the center.
(E) Range : is the simplest measure of distribution & indicates the "length" a distribution covers / it is determined by finding the difference between the lowest & highest value in a distribution.
(F) Interquartile Range : the difference between the third & first quartile and can be used to provide a measure of spread within a data set which includes extreme data values.
(G) Semi Interquartile Range : another measure of spread & is computed as one half of the interquartile range which contains half of the data values.
(H) Standard Deviation : the measure of spread most commonly used in statictics when the mean is used to calculate central tendency.
(I) Skewness : is a measure of the degree of asymmetry of a distribution.
(J) Kurtois : is a measure of whether the data are peaked or flat relative to a normal distributions.
(1) PENERANGAN
- setiap polisi yang dibuat hendaklah berdasarkan kepada fakta & bukan "khabar angin". Pihak KP / JPN hendaklah dapatkan data & bukti yang tepat sebelum buat sesuatu polisi
(2) PENYERTAAN BERSAMA
- semua pihak yang terlibat hendaklah turut serta dalam rancang polisi. Antaranya:
A. Pelajar
B. Guru
C. Pengetua
D. Ibu bapa
E. Ahli masyarakat
(3) TAKRIFAN MASALAH
- apabila nak buat polisi, semua pihak yang terlibat hendaklah bersetuju tentang apa yang dimaksudkan dengan tingkah laku yang tidak diingini
(4) HUKUMAN YANG FLEKSIBEL
- hukuman tidak perlu rigid,ia hendaklah berdasarkan kepada keadaan & kesalahan yang macam mana dilakukan
(5) PENGUATKUASAAN YANG SELARAS
- sekiranya pelajar fahami kod disiplin sekolah, mereka akan dilayan seadil-adilnya & penguatkuasaan daripada pihak sekolah hendaklah konsisten
