Collecting data is only half the job. The real value comes from reading it well: spotting the message in a table, drawing fair conclusions from a chart, and knowing the difference between what the data shows and what it merely suggests. Good interpretation is a skill that protects you from being misled.
In this lesson you will read and draw inferences from tables and statistical diagrams, compare two data sets using both an average and a measure of spread, and learn the limits of what data can honestly tell you. These critical-thinking skills matter far beyond the exam, in any situation where numbers are used to make a case.
Gbọ́ ẹ̀kọ́ yìí nínú áàpù
A ti ṣe àwòrán kókó yìí kí o lè rí bí àwọn èrò ṣe so pọ̀.
Ṣí àwòrán ọpọlọ nínú áàpù
Ìdánrawò kíákíá lórí ohun tí wọ́n ń dán wò nínú kókó yìí.
Ṣe ìdánrawò káàdì wọ̀nyí nínú áàpù
Gba ohun èlò Green Bridge CBT sórí fóònù tàbí kọ̀mpútà rẹ fún gbogbo ilé ìkàwé IGCSE: ìwé ìdánwò àtijọ́, ìlànà ìdíwọ̀n, àwòrán èrò, káàdì ìkẹ́kọ̀ọ́ àti ẹ̀kọ́ ohùn.
Oriire fun ipari ẹkọ lori Interpreting Statistical Data. Ni bayi ti o ti ṣawari naa awọn imọran bọtini ati awọn imọran, o to akoko lati fi imọ rẹ si idanwo. Ẹka yii nfunni ni ọpọlọpọ awọn adaṣe awọn ibeere ti a ṣe lati fun oye rẹ lokun ati ṣe iranlọwọ fun ọ lati ṣe iwọn oye ohun elo naa.
Iwọ yoo pade adalu awọn iru ibeere, pẹlu awọn ibeere olumulo pupọ, awọn ibeere idahun kukuru, ati awọn ibeere iwe kikọ. Gbogbo ibeere kọọkan ni a ṣe pẹlu iṣaro lati ṣe ayẹwo awọn ẹya oriṣiriṣi ti imọ rẹ ati awọn ogbon ironu pataki.
Lo ise abala yii gege bi anfaani lati mu oye re lori koko-ọrọ naa lagbara ati lati ṣe idanimọ eyikeyi agbegbe ti o le nilo afikun ikẹkọ. Maṣe jẹ ki awọn italaya eyikeyi ti o ba pade da ọ lójú; dipo, wo wọn gẹgẹ bi awọn anfaani fun idagbasoke ati ilọsiwaju.
Ṣiṣẹ́ lórí àwọn ìbéèrè wọ̀nyí nínú ohun èlò náà
Ṣiṣẹ́ lórí àwọn ìbéèrè wọ̀nyí nínú ohun èlò náà
One simple graph, the stem-and-leaf graph or stemplot , comes from the field of exploratory data analysis. It is a good choice when the data sets are small. To create the plot, divide each observation of data into a stem and a leaf. The stem consists of the leading digit(s), while the leaf consists
"Statistics: Stem-and-Leaf Graphs (Stemplots), Line Graphs, and Bar Graphs" by OpenStax, OpenStax, Rice University, licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). Source: https://openstax.org/books/statistics/pages/2-1-stem-and-leaf-graphs-stemplots-line-graphs-and-bar-graphs. Access for free at https://openstax.org/books/statistics/pages/1-introduction
An important characteristic of any set of data is the variation in the data. In some data sets, the data values are concentrated closely near the mean; in other data sets, the data values are more widely spread out from the mean. The most common measure of variation, or spread, is the standard devia
"Introductory Statistics: Measures of the Spread of the Data" by OpenStax, OpenStax, Rice University, licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). Source: https://openstax.org/books/introductory-statistics/pages/2-7-measures-of-the-spread-of-the-data. Access for free at https://openstax.org/books/introductory-statistics/pages/1-introduction
Àwọn àjọ mìíràn ló tẹ̀ wọ́n jáde lábẹ́ ìwé àṣẹ ṣíṣí, a sì dá wọn lọ́lá bí wọ́n ṣe béèrè. Àwọn ìjápọ̀ ń ṣí ojú òpó wọn.
Ṣe o fẹ ṣe adaṣe awọn ibeere idanwo adaṣe nipa Interpreting Statistical Data? Ṣe igbasilẹ ohun elo Green Bridge CBT lati wọle si awọn ibeere idanwo adaṣe ati awọn ayẹwo adaṣe kikun fun koko-ọrọ yii.
Gbogbo ohun ti o nilo lati ṣe dara julọ ninu JAMB, WAEC ati NECO.