So, in this particularly interesting lesson about pendulums on 12 February, we observed what happened when the length of the pendulum is systematically changed, which will then be a basis for making predictions about the motion of the pendulum!
Here is how the experiment went:
Firstly, we set up the experiment for the pendulum, a pendulum bob on a string that was clamped on to the retort stand. During the experiment, we observed the number of swings the pendulum made when the length of the pendulum of the pendulum was systematically changed at an interval of 10 centimetres apart.
Secondly, based on our observations, we had to predict the amount of swings the pendulum would make with the length of the string being changed with an interval of 5 centimetres. In addition to that, we also plotted a curve graph from our experiment results and also had to predict the amount of swings the pendulum would make.
Thirdly, we did carry out the experiment again, just that now the length of the string was systematically changed with an interval of 5 centimetres.
Out of this lad besson, we learned quite a few things. I did learn the concept that ":the greater the length of the pendulum, the longer the time taken for one oscillation.
Wednesday, 2 July 2014
Vernier Caliper, Micrometer Screw Gauge and Zero Error
On 18 February, it was one of those dull worksheet lessons in which we stayed in class to do worksheets. So, on that day,Mr Tan taught us how to use the
vernier caliper, and the micrometer screw gauge. In addition to that, before the lesson, we had attended an IVLE lesson in which it had also taught us on how to use the Vernier Caliper and the Micrometer Screw Gauge. Besides, we learnt about Zero Error, in which it means that the measuring instrument still has other measurements other than 0 when it is fully shut.
On 26 February, I managed to apply this knowledge of usage of vernier calipers and micrometer screw gauge. However, besides that, I also learnt the difference between Raw Data and Processed Data.
Raw Data are measurements taken directly from a measuring instrument. This is expressed to a fixed number of decimal places dictated by the units used and the precision of the instrument.
Processed Data are readings obtained from the calculations of one or more sets of raw data.
So, now back to what we did. We first measured the height of a seat using a metre ruler. Next, we measured the internal and external diameter of a beaker with a vernier caliper. Besides that, we also measure the diameter of a wire and a marble using the micrometer screw gauge.
All together, I learned how to use the vernier caliper and micrometer screw gauge. Besides that, i also ensured that the vernier caliper and micrometer screw gauge had no zero error at all!
Micrometer screw gauge
On 26 February, I managed to apply this knowledge of usage of vernier calipers and micrometer screw gauge. However, besides that, I also learnt the difference between Raw Data and Processed Data.
Raw Data are measurements taken directly from a measuring instrument. This is expressed to a fixed number of decimal places dictated by the units used and the precision of the instrument.
Processed Data are readings obtained from the calculations of one or more sets of raw data.
So, now back to what we did. We first measured the height of a seat using a metre ruler. Next, we measured the internal and external diameter of a beaker with a vernier caliper. Besides that, we also measure the diameter of a wire and a marble using the micrometer screw gauge.
All together, I learned how to use the vernier caliper and micrometer screw gauge. Besides that, i also ensured that the vernier caliper and micrometer screw gauge had no zero error at all!
Vernier caliper
Micrometer screw gauge
Tuesday, 1 July 2014
Kinetic Particle Theory, Brownian Motion and Diffusion
On 1 April 2014, the teacher taught us about the Kinetic Particle Theory, Brownian Motion and Diffusion.
So, What is the Kinetic Particle Theory? The Kinetic Particle Theory is a theory that states that matter is made up of large number of tiny particles (atoms or molecules), which are a continuous and random motion.
Besides, we also learnt about Brownian Motion! Brownian Motion is the continuous and random motion of small particles in fluids (liquids or gases). Brownian Motion involves 2 motions, a gas/liquid particle that is the particle that is moving continuously and randomly due to its kinetic energy. The other type of motion would be small solid particles that are bombarded by the gas particles in random directions, therefore causing it to move.
In addition, we learnt that Diffusion is the particles moving randomly from a region of a high concentration to lower concentration.
So, What is the Kinetic Particle Theory? The Kinetic Particle Theory is a theory that states that matter is made up of large number of tiny particles (atoms or molecules), which are a continuous and random motion.
Besides, we also learnt about Brownian Motion! Brownian Motion is the continuous and random motion of small particles in fluids (liquids or gases). Brownian Motion involves 2 motions, a gas/liquid particle that is the particle that is moving continuously and randomly due to its kinetic energy. The other type of motion would be small solid particles that are bombarded by the gas particles in random directions, therefore causing it to move.
In addition, we learnt that Diffusion is the particles moving randomly from a region of a high concentration to lower concentration.
Monday, 30 June 2014
Significant Figures and Decimal Points
On 12 February 2014, my Science teacher taught us about significant figures and decimal points!
Regarding the topic of significant figures, there are a few rules regarding significant figures.
Firstly, Non-zero digits are always significant.
Secondly, All final zeros after the decimal point are significant.
Thirdly, Zeros between two other significant digits are always significant.
Fourthly, Zeros used for only spacing the decimal are not significant.
Besides, I also learnt about the Calculation of Physical Data. I also did learn some news stuff to expand my knowledge!
For example, for Addition and Subtraction, The final value has the same number of decimal place / same place value as the least precise measurement.
For Multiplication and Division, The product / quotient has the same number of significant figures as the number with the least number of significant figures.
For Average, The final value has the same number of decimal place / same place value as the least precise measurement.
Meanwhile, for Constant, The number of decimal place / place value of a constant is not considered in a calculation.
In addition to this, I also learned about the accuracy of devices, the smallest division and the amount of uncertainty that each apparatus had!
Regarding the topic of significant figures, there are a few rules regarding significant figures.
Firstly, Non-zero digits are always significant.
Secondly, All final zeros after the decimal point are significant.
Thirdly, Zeros between two other significant digits are always significant.
Fourthly, Zeros used for only spacing the decimal are not significant.
Besides, I also learnt about the Calculation of Physical Data. I also did learn some news stuff to expand my knowledge!
For example, for Addition and Subtraction, The final value has the same number of decimal place / same place value as the least precise measurement.
For Multiplication and Division, The product / quotient has the same number of significant figures as the number with the least number of significant figures.
For Average, The final value has the same number of decimal place / same place value as the least precise measurement.
Meanwhile, for Constant, The number of decimal place / place value of a constant is not considered in a calculation.
In addition to this, I also learned about the accuracy of devices, the smallest division and the amount of uncertainty that each apparatus had!
Monday, 12 May 2014
Physical Quantities and Units
On 11 February 2014, my teacher taught us about physical quantities and units!
We learned that Observations and Variables are part of Physical Quantity,
So, what is physical quantity? Well, physical quantity can be measured and is made up of a base quantity and derived quantity.
Base Quantities are the building blocks of other physical quantities, such as metre, kilogram and etc.
So, the BASE QUANTITY, is also the SI unit (Symbol for Unit)
Derived Quantities are derived from base quantities through defining and equation.
As such, we need to have prefixes to represent the gigantic numbers and the very small numbers.
For example, we have prefixes such as "Tera" and "Giga" to describe large. and also "micro" and "milli" to describe very small numbers.
So, why do have Prefixes? Feel free to click on the links below!
We learned that Observations and Variables are part of Physical Quantity,
So, what is physical quantity? Well, physical quantity can be measured and is made up of a base quantity and derived quantity.
Base Quantities are the building blocks of other physical quantities, such as metre, kilogram and etc.
So, the BASE QUANTITY, is also the SI unit (Symbol for Unit)
Derived Quantities are derived from base quantities through defining and equation.
As such, we need to have prefixes to represent the gigantic numbers and the very small numbers.
For example, we have prefixes such as "Tera" and "Giga" to describe large. and also "micro" and "milli" to describe very small numbers.
So, why do have Prefixes? Feel free to click on the links below!
Lastly, we also learned about unit conversion.
Graphing Scientific Data
On 22 January 2014, we learned about how to graph scientific data.
Firstly, we learned about interpolation and extrapolation.In simple terms, interpolation is just a method used to approximate values that are between points of a graph, while extrapolation is a method for approximating values that are beyond the range of the measurements obtained.
So firstly, there is the BEST-FIT LINE. The best-fit line is basically a line that has roughly the same amount of points on each side of the line.
Secondly, there is a more advanced type of line, which is called the "Best Fit Curve". As the name suggests, we draw a smooth curved line through the points, not a straight line.
Firstly, we learned about interpolation and extrapolation.In simple terms, interpolation is just a method used to approximate values that are between points of a graph, while extrapolation is a method for approximating values that are beyond the range of the measurements obtained.
So firstly, there is the BEST-FIT LINE. The best-fit line is basically a line that has roughly the same amount of points on each side of the line.
Secondly, there is a more advanced type of line, which is called the "Best Fit Curve". As the name suggests, we draw a smooth curved line through the points, not a straight line.
Science Laboratory Lesson "Boiling Point of Water"
On 5 February 2014, we conducted an experiment regarding the boiling point of water, as mentioned in the above header.
Firstly, we learned how to read the thermometer properly, in which it is essential that the eye be at the same level as the mercury meniscus, so as to prevent parallax error.
Secondly, we carried out the experiment and we recorded the experiment results, placing the raw data into the tables. However, we noticed that the water had some impurities as the water boiled at 101.5 degrees Celsius.
Afterwards, we plotted the results on a graph, joining the points with a best fit curve, and we also learned how to make accurate predictions from the graph.
Firstly, we learned how to read the thermometer properly, in which it is essential that the eye be at the same level as the mercury meniscus, so as to prevent parallax error.
Secondly, we carried out the experiment and we recorded the experiment results, placing the raw data into the tables. However, we noticed that the water had some impurities as the water boiled at 101.5 degrees Celsius.
Afterwards, we plotted the results on a graph, joining the points with a best fit curve, and we also learned how to make accurate predictions from the graph.
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