To save content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about saving content to .
To save content items to your Kindle, first ensure no-reply@cambridge.org
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about saving to your Kindle.
Note you can select to save to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
The purpose of this chapter is to give readers a feel for how experiments are designed, implemented, and analyzed. The chapter walks through the steps of designing a small, inexpensive experiment that can be conducted at home. We will also discuss the fine points of implementing an experiment, assembling a dataset, and preparing a statistical analysis. In order to put aside ethical and procedural issues that apply to experiments involving human participants, this chapter confines its attention to product testing. Drawing inspiration from the first field experiments conducted a century ago, my running example will test the effects of fertilizer on plant growth.] As I design and implement my experiment, I call attention to small but consequential decisions aimed at preventing violations of core assumptions. The final section of the chapter describes some illustrative experiments conducted by students, and the exercises provide their data so that you can retrace their steps.
Verbs in Aramaic can express different semantic features morphologically and syntactically. The inflectional system (the finite conjugations, and the non-finite forms) signifies the features of tense, aspect, and mood.
The band theory of solids provides a general framework with which to understand properties of materials. It not only explains the fundamental differences in electronic structure between insulators, semiconductors, and metals but also provides guidelines for finding optimum materials for specific device applications. For example, a semiconductor with a light effective mass is suited for high-electron-mobility transistors (HEMTs) because the mobility is inversely proportional to the effective mass, , where τ is the scattering time. For developing LEDs and laser diodes, a direct band gap material – i.e., a material in which the conduction-band bottom and the valence-band top occur at the same k – is necessary for momentum conservation since the momentum of photons is negligibly small compared with crystal momenta. In this chapter, after reviewing the basic concepts of atomic and molecular orbitals, bonds and bands, crystal lattices and reciprocal lattices, we provide an overview of the band structure of technologically important materials, including both traditional and emerging materials.
Derivational verbal bases, like those of nouns and adjectives, are built by combining the root morpheme (usually of three consonants) with a pattern of vowels and other modifications. The root + pattern base in verbs is organized into a group of verbal stems, which form a syntactic–semantic system. Various default settings of valence (§323), voice (§325), and Aktionsart (§328) are assigned to particular stems, although these settings can be neutralized or set aside in particular cases.
The linking of a main clause to a second, dependent clause which modifies the main clause adverbially is subordination. The linking is usually marked by a subordinating conjunction, although in some cases a coordinating conjunction is used, and the subordination is semantic rather than syntactic.
This chapter introduces key terms used to describe experiments and, more generally, the investigation of cause and effect. Because so many different disciplines use experiments, layers of overlapping terminology have accumulated, and this chapter tries to cut through the clutter by grouping synonyms, thereby keeping jargon to a minimum. In addition to providing definitions, this chapter explains why these key concepts are important in practice. The chapter starts with the basic ingredients of an experiment (treatments, outcomes). Next, we define what we mean by a causal effect, introducing the concept of potential outcomes. The chapter culminates in the presentation of three core assumptions for unbiased causal inference. These core assumptions figure prominently throughout the book, as readers are continually encouraged to assess whether illustrative experiments satisfy these assumptions in practice.
Prior chapters relied on elementary statistical calculations and base R functions to analyze and visualize experimental results. This chapter builds on this foundation by showing how covariate adjustment using regression can be used to improve the precision with which treatment effects are estimated. Readers are shown how to apply regression to actual experimental data and to visualize multivariate regression results using R packages. This chapter also introduces the concepts of substantive and statistical “significance,” calling attention to the distinction between estimates of the average treatment effect that are large enough to be meaningful, even if they are not statistically distinguishable from zero. Examples of this distinction are provided using actual experimental data.
Independent personal pronouns are differentiated by person, gender, and number. They serve primarily as the subjects of copular and verbal clauses (§353). The 3mp/3fp pronouns also serve as direct objects in lieu of a dedicated 3mp object suffix.