![]() The original estimates also contains the influence of the irregular component. In a similar way, any changes to seasonal patterns might also be ignored. If the two consecutive months of March have different composition of trading days, it might reflect different levels of activity in original terms even though the underlying level of activity is unchanged. The comparison also ignores trading day effects. A comparison of these two months will not reflect the underlying pattern of the data. Easter occurs in April for most years but if Easter falls in March, the level of activity can vary greatly for that month for some series. This comparison ignores the moving holiday effect of Easter. compare the level of the original series observed in March for 20. For example, consider a comparison between two consecutive March months i.e. Also, year to year values will be biased by any changes in seasonal patterns that occur over time. Certain holidays such as Easter and Chinese New Year fall in different periods in each year, hence they will distort observations. WHY CAN'T WE JUST COMPARE ORIGINAL DATA FROM THE SAME PERIOD IN EACH YEAR?Ī comparison of original data from the same period in each year does not completely remove all seasonal effects. Observed data needs to be seasonally adjusted as seasonal effects can conceal both the true underlying movement in the series, as well as certain non-seasonal characteristics which may be of interest to analysts. Seasonal adjustment is the process of estimating and then removing from a time series influences that are systematic and calendar related. WHAT IS SEASONAL ADJUSTMENT AND WHY DO WE NEED IT? Other seasonal effects include trading day effects (the number of working or trading days in a given month differs from year to year which will impact upon the level of activity in that month) and moving holiday (the timing of holidays such as Easter varies, so the effects of the holiday will be experienced in different periods each year). Some examples include the sharp escalation in most Retail series which occurs around December in response to the Christmas period, or an increase in water consumption in summer due to warmer weather. Both types of series can still be seasonally adjusted using the same seasonal adjustment process.Ī seasonal effect is a systematic and calendar related effect. The main difference between a stock and a flow series is that flow series can contain effects related to the calendar (trading day effects). Manufacturing is also a flow measure because a certain amount is produced each day, and then these amounts are summed to give a total value for production for a given reporting period. For example, surveys of Retail Trade activity. For example, the Monthly Labour Force Survey is a stock measure because it takes stock of whether a person was employed in the reference week.įlow series are series which are a measure of activity over a given period. Time series can be classified into two different types: stock and flow.Ī stock series is a measure of certain attributes at a point in time and can be thought of as “stocktakes”. ![]() Data collected irregularly or only once are not time series.Īn observed time series can be decomposed into three components: the trend (long term direction), the seasonal (systematic, calendar related movements) and the irregular (unsystematic, short term fluctuations). This is because sales revenue is well defined, and consistently measured at equally spaced intervals. For example, measuring the value of retail sales each month of the year would comprise a time series. ![]() ![]() Want to change the area unit? Simply click on the unit name, and a drop-down list will appear.A time series is a collection of observations of well-defined data items obtained through repeated measurements over time. ![]() Regular polygon area formula: A = n × a² × cot(π/n) / 4.Quadrilateral area formula: A = e × f × sin(angle).Octagon area formula: A = 2 × (1 + √2) × a².Hexagon area formula: A = 3/2 × √3 × a².Trapezoid area formula: A = (a + b) × h / 2.Circle sector area formula: A = r² × angle / 2.For the sake of clarity, we'll list the equations only - their images, explanations and derivations may be found in the separate paragraphs below (and also in tools dedicated to each specific shape).Īre you ready? Here are the most important and useful area formulas for sixteen geometric shapes: Well, of course, it depends on the shape! Below you'll find formulas for all sixteen shapes featured in our area calculator. ![]()
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