Sampling Methods: Statistics Overview

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Questions and Answers

Dalam konteks persampelan statistik, apakah tujuan utama memilih sampel daripada populasi yang lebih besar?

  • Untuk mengelakkan bias persampelan sama sekali.
  • Untuk mengurangkan ketepatan dan kecekapan penyelidikan.
  • Untuk meningkatkan kos dan masa yang diperlukan untuk mengumpul data.
  • Untuk membuat inferens tentang ciri-ciri seluruh populasi. (correct)

Istilah manakah yang menerangkan senarai atau sumber yang digunakan untuk mengenal pasti dan mengakses populasi untuk tujuan persampelan?

  • Bias persampelan
  • Kerangka persampelan (correct)
  • Unit persampelan
  • Ralat persampelan

Kecenderungan sistematik dalam proses persampelan yang menyebabkan sampel tidak mewakili populasi dengan tepat dikenali sebagai apakah?

  • Ralat persampelan
  • Bias persampelan (correct)
  • Variasi persampelan
  • Ralat rawak

Dalam persampelan kebarangkalian, apakah ciri yang menentukan?

<p>Setiap ahli populasi mempunyai kebarangkalian yang diketahui dan bukan sifar untuk dipilih. (A)</p> Signup and view all the answers

Kaedah persampelan manakah yang membahagikan populasi kepada subkumpulan (strata) dan memilih sampel rawak daripada setiap subkumpulan?

<p>Persampelan berstrata (B)</p> Signup and view all the answers

Persampelan mudah ialah kaedah persampelan bukan kebarangkalian. Apakah yang mencirikan kaedah ini?

<p>Memilih ahli yang mudah diakses dan sedia ada. (C)</p> Signup and view all the answers

Dalam persampelan kuota, ahli dipilih berdasarkan apakah?

<p>Memenuhi kuota yang telah ditetapkan berdasarkan ciri demografi. (C)</p> Signup and view all the answers

Apakah kesan kebolehubahan populasi terhadap saiz sampel?

<p>Populasi yang lebih heterogen memerlukan saiz sampel yang lebih besar. (C)</p> Signup and view all the answers

Bagaimanakah tahap keyakinan yang diingini mempengaruhi saiz sampel?

<p>Tahap keyakinan yang lebih tinggi memerlukan saiz sampel yang lebih besar. (A)</p> Signup and view all the answers

Dalam konteks saiz sampel, apakah itu margin ralat yang boleh diterima?

<p>Margin ralat yang lebih kecil memerlukan saiz sampel yang lebih besar. (B)</p> Signup and view all the answers

Apabila saiz populasi menjadi sangat besar, apakah yang berlaku kepada kesan saiz populasi pada saiz sampel?

<p>Kesan berkurangan. (A)</p> Signup and view all the answers

Dalam pertimbangan etika dalam persampelan, apakah yang dimaksudkan dengan informed consent?

<p>Mendapatkan informed consent daripada peserta sampel sebelum mengumpul data. (A)</p> Signup and view all the answers

Bagaimanakah penyelidik harus melindungi kerahsiaan dan privasi peserta sampel?

<p>Dengan mengumpul data tanpa nama dan menggunakan prosedur selamat untuk menyimpan data. (A)</p> Signup and view all the answers

Mengapakah keadilan dan kesaksamaan penting dalam proses persampelan?

<p>Untuk memastikan bahawa proses pensampelan adalah adil dan sama rata, dan tidak mendiskriminasi mana-mana kumpulan. (C)</p> Signup and view all the answers

Apakah aplikasi persampelan dalam penyelidikan tinjauan?

<p>Untuk mengumpul data daripada sampel individu untuk membuat inferens tentang populasi yang lebih besar. (D)</p> Signup and view all the answers

Dalam kajian klinikal, apakah tujuan menggunakan persampelan?

<p>Untuk menilai keberkesanan dan keselamatan rawatan perubatan. (C)</p> Signup and view all the answers

Bagaimanakah persampelan digunakan dalam ujian produk?

<p>Untuk menilai kualiti dan penerimaan produk. (C)</p> Signup and view all the answers

Dalam kawalan kualiti, apakah tujuan persampelan?

<p>Untuk memantau dan mengawal kualiti proses pengeluaran. (A)</p> Signup and view all the answers

Apakah peranan persampelan dalam penyelidikan pasaran?

<p>Untuk memahami keutamaan dan tingkah laku pelanggan. (D)</p> Signup and view all the answers

Persampelan bola salji ialah satu kaedah dimana?

<p>Ahli dipilih melalui rujukan daripada ahli yang sedia ada (A)</p> Signup and view all the answers

Flashcards

What is sampling?

A statistical method to select a subset from a larger population to estimate its characteristics.

Purpose of sampling

To make inferences about a large population based on smaller observations, reducing costs and improving research accuracy.

Population

The entire group of individuals, objects, or items of interest in a study.

Sample

A subset of the population selected for analysis.

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Sampling frame

A list or source used to identify and access the population.

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Sampling bias

A systematic tendency causing the sample to misrepresent the population.

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Sampling error

Natural variation when a sample is used to infer about a population.

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Probability sampling

Each population member has a known, non-zero probability of being selected.

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Simple random sampling

Each population member has an equal chance of being selected.

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Systematic sampling

Selecting members from the population at a regular interval.

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Stratified sampling

Dividing the population into subgroups (strata) and randomly sampling from each.

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Cluster sampling

Dividing the population into clusters, randomly selecting clusters, and sampling all members within selected clusters.

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Non-probability sampling

Population members are selected based on subjective criteria, not random probabilities.

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Convenience sampling

Selecting members who are easily accessible and available.

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Judgment sampling

Selecting members based on the researcher's judgment or expertise.

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Quota sampling

Selecting members to meet pre-set quotas based on demographic characteristics.

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Snowball sampling

Selecting members through referrals from existing members.

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Factors affecting sample size

Variability of the population, desired confidence level, and acceptable margin of error.

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Ethical considerations in sampling

Obtaining informed consent, protecting confidentiality, minimizing harm, and ensuring fairness.

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Applications of sampling

Survey research, clinical trials, product testing, quality control, and market research.

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Study Notes

  • Sampling is a statistical method used to select a subset of individuals (a sample) from a larger population to estimate characteristics of the whole population.

Purpose of Sampling

  • Allows researchers to make inferences about a large population based on smaller observations
  • Reduces the costs, time, and resources required for data collection
  • Increases the accuracy and efficiency of research
  • Population: The entire group of individuals, objects, or items of interest
  • Sample: A subset of the population selected for analysis
  • Sampling unit: A single individual or item in the population
  • Sampling frame: A list or source used to identify and access the population
  • Sampling bias: A systematic tendency in the sampling process that results in a sample not accurately representing the population
  • Sampling error: The natural variation that occurs when a sample is used to make inferences about a population

Types of Sampling Methods

  • Probability Sampling: Each member of the population has a known and non-zero probability of being selected
    • Simple Random Sampling: Every member of the population has an equal chance of being selected
    • Systematic Sampling: Selecting members from the population at a regular interval
    • Stratified Sampling: Dividing the population into subgroups (strata) and selecting a random sample from each stratum
    • Cluster Sampling: Dividing the population into clusters and randomly selecting clusters, sampling all members within the selected clusters
  • Non-Probability Sampling: Members of the population are selected based on subjective criteria, rather than random probabilities
    • Convenience Sampling: Selecting members who are easily accessible and readily available
    • Judgment Sampling: Selecting members based on the researcher's judgment or expertise
    • Quota Sampling: Selecting members to meet pre-set quotas based on demographic characteristics
    • Snowball Sampling: Selecting members through referrals from existing members

Factors Affecting Sample Size

  • Variability of the population: More heterogeneous populations require larger sample sizes
  • Desired level of confidence: Higher levels of confidence require larger sample sizes
  • Acceptable margin of error: Smaller margins of error require larger sample sizes
  • Population size: Larger populations may require larger sample sizes, but the effect diminishes as the population size becomes very large

Ethical Considerations in Sampling

  • Informed consent: Obtaining informed consent from sample participants before collecting data
  • Confidentiality and privacy: Protecting the confidentiality and privacy of sample participants
  • Minimizing harm: Avoiding causing physical or psychological harm to sample participants
  • Fairness and equity: Ensuring that the sampling process is fair and equitable, and does not discriminate against any groups

Applications of Sampling

  • Survey research: To collect data from a sample of individuals to make inferences about a larger population
  • Clinical trials: To evaluate the effectiveness and safety of medical treatments
  • Product testing: To assess the quality and acceptance of products
  • Quality control: To monitor and control the quality of production processes
  • Market research: To understand customer preferences and behavior

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