Systematic Sampling

Definition-

Any sample drawn from a list using a random start and a fixed sampling interval. This differs from simple random sampling in not giving equal probability of selection to all possible samples which could be taken from the population. This method is widely used in the UK. This type of sampling involves calculating the sample interval, by finding the ratio of the population to the sample. A random number is then chosen between 1 and the sampling interval. ...

Meaning-

Methodology for sampling in which units are selected from the population at a regular interval (e.g., once an hour, every other lot, etc.). ! From the sampling frame, a starting point is chosen at random, and thereafter at regular intervals.
For example,
Suppose you want to sample 8 houses from a street of 120 houses.
120/8=15, so every 15th house is chosen after a random starting point between 1 and 15. If the random starting point is 11, then the houses selected are 11, 26, 41, 56, 71, 86, 101, and 116. If there were 125 houses, 125/8=15.625, so should you take every 15th house or every 16th house? If you take every 16th house, 8*16=128 so there is a risk that the last house chosen does not exist. To overcome this the random starting point should be between 1 and 10. On the other hand if you take every 15th house, 8*15=120 so the last five houses will never be selected. The random starting point should now be between 1 and 20 to ensure that every house has some chance of being selected.

Systematic sampling is especially useful in situations when you want to:

• Sample over extended periods of time.
• Reduce the impact of a variety of conditions to prevent systematic errors from influencing the analysis of the data.
• One reason for this type of sampling is to see if the process has any variations due to different times of the day, shift workers changing, temperature changes during day vs. night times, etc.

Advantages.
Spreads the sample more evenly over the population
easier to conduct than a simple random sample
Easier, faster and less chance of making a sampling mistake, compared with SRS.
Could give a more precise estimate than SRS.

Disadvantages
the system may interact with some hidden pattern in the population, e.g. every third house along the street might always be the middle one of a terrace of three
Could be less precise than SRS
Effect of periodicity (bias caused by particular characteristics arising in the sampling frame at regular units). An example of this would occur if you used a sampling frame of adult residents in an area composed of predominantly couples or young families. If this list was arranged: Husband / Wife / Husband / Wife etc. and if every tenth person was to be interviewed, there would be an increased chance of males being selected.

Simple random sampling Vs Convinience sampling

Sampling random sampling
1) Every individual has equal chance of getting selected
2) Items are selected randomly
3) Individuals are selected without bias
4) Results can be applied/generalized to the population

Convenience sampling
1) Nearest individuals are chosen to serve as sample participants
2) Items are selected purposively
3) Individuals are selected with bias
4) Results/findings cannot be generalized to the population

Lets Discuss!!!!!

C - Communication
O - Obviously

M -Means

M - Most

U - Understand

N - Nearly
I - In total

C - Clearly

A - All

T - Than an

I - Individual

O - Offers to

N - Narrate

"Our first responsibility as effective listeners is to understand ourselves as communicators. Just as the sources of the communication message should be trained in self-intrapersonal communication, so, too, should listeners know themselves." --- Carolyn Coakley

"It was impossible to get a conversation going, everybody was talking too much." --Yogi Berra

"Effective communications starts with listening." --Robert Gately

"Good communication is as stimulating as black coffee and just as hard to sleep after." -- Anne Morrow Lindbergh

Nokia - "Connecting People"

Go and measure practicality

Hi,
I am not sure about the answer

• Goal Orientation- Researcher sets a goal and to achieve that a goal objectives are specified. So sample should be designed in such a way that all objectives are achieved and hence the goal.
• Measurability- Measurability is related to sample size i.e. sample size should not be large or too small it should be manageable or it may be related to different variables of sample. Those variables should be measurable.
• Practicality – practicality is related to practicality of research i.e. it can be conducted on that sample.
• Economy- Again economy will depend upon sample size. Larger the sample size larger the economy or vice versa. So while selecting sample researcher should keep this thing in mind.
  

Accessibility of samples

• Sample itself may not be available for research, may be due to lack of time or may be due to their exams. or their parents may not allow researcher to conduct a research.
• Some times it might happen that the information that the authorities have is not to be disclosed i.e they will not share information with you, researcher can face such kind of problem.

Hi Thats me!!!!!!!!!!

hi everybody!!!! This is Jailee. It was great to know about this blog.
It was great experience while making this blog. I can share my work in this blog. I think this a space where I can learn many things.